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There have been many progresses in the stereo matching problem. However, some remaining problems still make stereo matching difficult. Occlusion is one of such problems. In this paper, we propose a new stereo matching model that addresses this problem by using an effective visibility constraint. By considering two images simultaneously, complex geometric configurations regarding the visibility of a pixel becomes simplified, so that the visibility constraint can be modeled as a pairwise MRF. Also since the proposed model enforces the consistency between two disparity maps, the final results become consistent with each other. Belief propagation is employed for the solution of the modeled pairwise MRF. Experimental results on the standard data set demonstrate the effectiveness of our approach. [ABSTRACT FROM AUTHOR]

Many industrial applications involve rotations. Different from traditional measurements, we propose a novel vision method based on image motion blur to estimate angular velocity and angular displacement in this paper. First, we transform 2D rotation to 1D translational motion by sectoring rotation blurred image. Then we use mathematical models in spatial and frequency domain to analyze translation blurred images. According to mathematical models in frequency domain, there is a series of dark parallel lines on the spectrum of the translation blurred image. These dark lines are exactly related to the velocity of translation and exposure time. Furthermore, based on the geometric relationship between rotation and translation, these dark lines are also related to angular velocity. Both simulation results and real experimental results, based on the proposed method in this paper, are provided. These results demonstrate the feasibility and efficiency of proposed method. [ABSTRACT FROM AUTHOR]

Stereo correspondence is one of the basic and most important problems in computer vision. For better correspondence, we need to determine the occlusion. Recently dynamic programming on a minimal span tree (mst) structure is used to search for correspondence. We have extended this idea. First, mst is generated directly based on the color information in the image instead of converting the color image into a gray scale. Second, have treated this mst as a Bayesian Network. Novelty is attained by considering local variances of the disparity and intensity differences in the conditional Gaussians as unobserved random parameters. These parameters are iteratively inferenced by alternate estimation along the tree given a current disparity map. It is followed by dynamic programming estimation of the map given the current variance estimates thus reducing the overall occlusion. We evaluate our algorithm on the benchmark Middlebury database. The results are promising for modeling occlusion in early vision problems. [ABSTRACT FROM AUTHOR]

We propose a scanline energy minimization algorithm for stereo vision. The proposed algorithm differs from conventional energy minimization techniques in that it focuses on the relationship between local match cost solution and the energy minimization solution. The local solution is transformed into energy minimization solution through the optimization of the disparity discontinuity. In this paper, disparity discontinuities are targeted during the energy minimization instead of the disparities themselves. By eliminating and relocating the disparity discontinuities, the energy can be minimized in iterations of O(n) where n is the number of pixels. Although dynamic programming has been adequate for both speed and performance in the scan-line stereo, the proposed algorithm was shown to have better performance with comparable speed. [ABSTRACT FROM AUTHOR]

In this paper we propose a new segment-based stereo matching algorithm using scene hierarchical structure. In particular, we highlight a previously overlooked geometric fact: the most foreground objects can be easily detected by intensity-based cost function and the farer objects can be matched using local occlusion model constructed by former recognized objects. Then the scene structure is achieved from foreground to background. Two occlusion relations are proposed to establish occlusion model and to update cost function. Image segmentation technique is adopted to increase algorithm efficiency and to decrease discontinuity of disparity map. Experiments demonstrate that the performance of our algorithm is among the state of the art stereo algorithms on various data sets. [ABSTRACT FROM AUTHOR]

A method to calibrate camera from a single frame of planar pattern is presented in this paper. For a camera model with four intrinsic parameters and visible lens distortion, the principal point and distortion coefficients are firstly determined through analysis of the distortion in an image. The distortion is then removed. Finally, the other intrinsic and extrinsic parameters of the camera are obtained through direct linear transform followed by bundle adjustment. Theoretically, the method makes it possible to analyze the calibration result at the level of a single frame. Practically, such a method provides a easy way to calibrate a camera used in industrial vision system on line and used in desktop vision system. Experimental results of both simulated data and real images validate the method. [ABSTRACT FROM AUTHOR]

Choosing the adequate registration and simulation parameters in non-parametric image registration methods is an open question. There is no agreement about which are the optimal values (if any) for these parameters, since they depend on the images to be registered. As a result, in the literature the parameters involved in the registration process are arbitrarily fixed by the authors. The present paper is intended to address this issue. A two-step method is proposed to obtain the optimal values of these parameters, in terms of achieving in a minimum number of iterations the best trade-off between similarity of the images and smoothness of the transformation. These optimal values minimize the joint energy functional defined in a variational framework. We focus on the specific formulation of diffusion and curvature registration, but the exposed methodology can be directly applied to other non-parametric registration schemes. The proposed method is validated over different registration scenarios. [ABSTRACT FROM AUTHOR]

The advances in robotics and imaging technologies have brought various imaging devices to the field of the unmanned exploration of new environments. Forward looking sonar is one of the newly emerging imaging methods employed in the exploration of underwater environments. While the video sequences produced by forward looking sonar systems are characterized by low signal-to-noise ratio, low resolution and limited range of sight, it is expected that video enhancement techniques will facilitate the interpretation of the video sequences. Since the video enhancement techniques for forward looking sonar video sequences are applicable to most of the forward looking sonar sequences, the development of such techniques is more crucial than developing techniques for optical camera video enhancement, where only specially produced video sequences can benefit the techniques. In this paper, we introduce a procedure to enhance forward looking sonar video sequences via incorporating the knowledge of the target object obtained in previously observed frames. The proposed procedure includes inter-frame registration, linearization of image intensity, and maximum a posteriori fusion of images in the video sequence. The performance of this procedure is verified by enhancing video sequences of Dual-frequency Identification Sonar (DIDSON), the market leading forward looking sonar system. [ABSTRACT FROM AUTHOR]

In this paper, we propose a new deinterlacing method using motion estimation and compensation of edge regions. Although motion-compensated deinterlacing methods provide significant results in interlaced-to-progressive conversion, they still have undesirable artifacts in fast moving areas and edge regions. The proposed method mitigates the problems by applying the edge region motion estimation and compensation with properly small search range. After filling the missing lines with the conventional spatial and temporal methods, motion estimation and compensation is applied to the predefined edge areas. Experimental results show that the proposed method produces noticeable improvement more than existing motion-compensated deinterlacing methods. [ABSTRACT FROM AUTHOR]

In the context of Universal Multimedia Access, efficient techniques are needed for the adaptation of video content. An important example is the reduction of the bitrate in order to satisfy the bandwidth constraints imposed by the network or the decoding capability of the terminal devices. Requantization transcoding is a fast technique for bitrate reduction, and has been successfully applied in previous video coding standards such as MPEG-2. In this paper, we examine requantization in H.264/AVC, focusing on the intra 16×16 prediction modes. Due to the newly introduced coding tools in H.264/AVC, new techniques are needed that are able to lower the bitrate at a minimal quality loss. We propose two novel architectures, one in the pixel domain and one in the frequency domain, that reuse the information from the incoming bitstream in an efficient way, and perform approximately equally well as a cascade of decoder and encoder. Due to their low computational complexity, the introduced architectures are highly suitable for on-the-fly video adaptation scenarios. [ABSTRACT FROM AUTHOR]

Content analysis of video and still images is attractive for multiple reasons, such as enabling content-based actions and image manipulation. This paper presents a new algorithm and feature model for blue-sky detection. The algorithm classifies the sky areas by computing a pixel-accurate sky probability. Such a probabilistic measure matches well with the requirements of typical video enhancement functions in TVs. This algorithm enables not only content-adaptive picture quality improvement, but also more advanced applications such as content-based annotation of, and retrieval from image and video databases. When compared to existing algorithms, our proposal shows considerable improvements in correct detection/rejection rate of sky areas, and an improved consistency of the segmentation results. [ABSTRACT FROM AUTHOR]

In this paper, we present a real-time sports analysis system, which not only recognizes the semantic events, but also concludes the behavior, like player's tactics. To this end, we propose an advanced multiple-player tracking algorithm, which addresses two improvements on practical problems: (1) updating of the player template so that it remains a good model over time, and (2) adaptive scaling of the template size depending on the player motion. In this algorithm, we obtain the initial locations of players in the first frame. The tracking is performed by considering both the kinematic constraints of the player and the color distribution of appearance, thereby achieving promising results. We demonstrate the performance of the proposed system by evaluating it for double tennis matches where the player count and the resulting occlusions are challenging. [ABSTRACT FROM AUTHOR]

Facial expression hallucination is an important approach to facial expression synthesis. Existing works mainly focused on synthesizing a static facial expression image given one face image with neutral expression. In this paper, we propose a novel two-level hierarchical fusion approach to hallucinate dynamic expression video sequences when given only one neutral expression face image. By fusion of local linear and global nonlinear subspace learning, the two-level approach provides a sound solution to organizing the complex video sample space. Experiments show that our approach generates reasonable facial expression sequences both in temporal domain and spatial domain with less artifact compared with existing works. [ABSTRACT FROM AUTHOR]

Disparity estimation can be used to eliminate redundancy among different views in multi-view video compression to obtain high compression efficiency. However, the problem of high computational complexity in disparity estimation, which limits real-time applications of multi-view systems, needs to be solved. In this paper, a novel fast multi-view disparity estimation algorithm based on Hadamard similarity coefficient for multi-view video coding is proposed by using prediction of initial search point, selection of reference view, determination of the best disparity vector, and strategies of search stop. Experimental results show that the proposed algorithm can significantly reduce the computational complexity in multi-view disparity estimation. [ABSTRACT FROM AUTHOR]

This paper presents an implementation of a color-based multiple agent tracking algorithm targeted for wireless image sensor networks. The proposed technique is based on employing lightweight algorithms and low-bandwidth data communication between multiple network nodes to track the path of autonomous agents moving across the fields of view (FOV) of the sensors. Segmentation techniques are applied to find the agents within the FOV, and a color histogram is constructed using the hue values of the pixels corresponding to agents. This histogram is used as a means of identification within the network. As such, the algorithm is able to reliably track multi-colored agents of irregular shapes and sizes and can resolve identities after collisions. The proposed algorithm has low computational requirements and its complexity scales linearly with the size of the network, so it is feasible in low-power, large-scale wireless sensor networks. [ABSTRACT FROM AUTHOR]

In this paper, we present AddCanny, an Anisotropic Diffusion and Dynamic reformulation of the Canny edge detector. The proposal provides two modifications to classical Canny detector. The first one consists of using an anisotropic diffusion filter instead of a Gaussian filter as Canny does in order to obtain better edge detection and location. The second one is the replacement of the hysteresis step by a dynamic threshold process, in order to reduce blinking effect of edges during successive frames and, therefore, generate more stable edges in sequences. Also, a new performance measurement based on the Euclidean Distance Transform to evaluate the consistency of computed edges is proposed. The paper includes experimental evaluations with different video streams that illustrate the advantages of AddCanny compared to classical Canny edge detector. [ABSTRACT FROM AUTHOR]

The H.264/AVC standard is a video compression standard that was jointly developed by the ITU-T Video Coding Experts Group and the ISO/IEC Motion Picture Experts Group. The H.264 video coding standard uses new coding tools, such as variable block size, quarter-pixel-accuracy motion estimation, intra prediction and a loop filter. Using these coding tools, H.264 achieves significant improvement in coding efficiency compared with existing standards. Encoder complexity, however, also increases tremendously. Among the tools, macroblock mode selection and motion estimation contribute most to total encoder complexity. This paper focuses on complexity reduction in macroblock mode selection. Of the macroblock modes which can be selected, inter8×8 and intra4×4 have the highest complexity. We propose two methods for complexity reduction of inter8×8 and intra4×4 by using the costs of the other macroblock modes. Simulation results show that the proposed methods save about 55% and 74% of total encoding time compared with the H.264 reference implementation when using a full search and a fast motion estimation scheme, respectively, while maintaining comparable PSNR. [ABSTRACT FROM AUTHOR]

Because of limitation of low power and computational ability in mobile video devices, it is significant to develop energy-efficient wireless video compression methods for mobile video systems. In this paper, a new approach to low complexity wireless video compression is proposed, based on Wyner-Ziv coding theorem. The proposed method encodes video only by intracoding techniques and detection of regions of interest, without the complicated motion estimation and compensation in the mobile video terminal. Thus, the computational burden is obviously reduced and the requirement of low power can be satisfied in mobile video devices. Experimental results show that the proposed method is quite effective. [ABSTRACT FROM AUTHOR]

We propose a detection method of corner outlier artifacts and a simple and effective filter in order to remove the artifacts in highly compressed video. We detect the corner outlier artifacts based on the direction of edges going through a block corner and the properties of blocks around the edges. Based on the detection results, we remove the stair-shaped discontinuities, i.e., corner outlier artifacts, using the neighboring pixels of the corner outlier artifact in the spatial domain. Simulation results show that the proposed method improves, particularly in combination with a deblocking filter, both objective performance and subjective visual quality. Keywords: corner outlier artifact, MPEG-4 video, deblocking filter, highly compressed video. [ABSTRACT FROM AUTHOR]

In many application scenarios, the use of Regions of Interest (ROIs) within video sequences is a useful concept. It is shown in this paper how Flexible Macroblock Ordering (FMO), defined in H.264/AVC as an error resilience tool, can be used for the coding arbitrary-shaped ROIs. In order to exploit the coding of ROIs in an H.264/AVC bitstream, a description-driven content adaptation framework is introduced that is able to extract the ROIs of a given bitstream. The results of a series of tests indicate that the ROI extraction process significantly reduces the bit rate of the bitstreams and increases the decoding speed. In case of a fixed camera and a static background, the impact of this reduction on the visual quality of the video sequence is negligible. Regarding the adaptation framework itself, it is shown that in all cases, the framework operates in real time and that it is suited for streaming scenarios by design. [ABSTRACT FROM AUTHOR]

Scalable wavelet-based video codecs based on motion-compensated temporal filtering (MCTF) require complexity scalability to cope with the growing heterogeneity of devices on which video has to be processed. The computational and memory complexity of two spatial-domain (SD) MCTF and in-band (IB) MCTF video codec instantiations are examined in this paper. Comparisons in terms of complexity versus performance are presented for both types of codecs. Some of the trade-offs between complexity and coding performance are analyzed and it is indicated how complexity scalability can be achieved in such video-codecs. Furthermore, a new approach is presented to obtain complexity scalability in IBMCTF video coding, by targeting the complexity of the complete-to-overcomplete discrete wavelet transform at the cost of a limited and controllable penalty on the overall coding performance. [ABSTRACT FROM AUTHOR]

This article presents a new algorithm for spatial deinterlacing that could easily be integrated in a more complete deinterlacing system, typically a spatio-temporal motion adaptive one. The spatial interpolation part often fails to reconstruct close to horizontal lines with a proper continuity, leading to highly visible artifacts. Our system preserves the structure continuity taking into account that the mis-interpolated points usually correspond to local value extrema. The processing is based on chained lists and connected graph construction. The new interpolation method is restricted to such structures, for the rest of the image, a proper traditional directional spatial interpolation gives satisfactory results already. Although the number of pixels affected by the extrema interpolation is relatively small, the overall image quality is subjectively well improved. Moreover, our solution allows to gain back one of the major advantages of motion compensation methods, without having to afford their complexity cost. [ABSTRACT FROM AUTHOR]

The emerging H.264/AVC video coding standard improves coding performance significantly by adopting many advanced techniques. This is achieved at the expense of great increase of encoder complexity. Specifically, the intra prediction using RDO examines all possible combinations of coding modes, which depend on spatial directional correlation with adjacent blocks. There are 9 modes for a 4×4 luma block, and 4 modes for a 16×16 luma block and an 8×8 chroma block, respectively. Therefore the number of mode combinations for each MB is 592. This paper proposes a complexity reduction algorithm using simple directional masks and neighboring modes. The proposed method reduces the number of mode combinations into 132 at the most. Simulation results show the proposed method reduces the encoding time up to 70% with negligible loss of PSNR and bit-rate increase compared with the H.264/AVC exhaustive search. Keywords: intra mode selection, intra prediction, H.264/AVC, RDO [ABSTRACT FROM AUTHOR]

H.264 adopts new coding tools such as intra-prediction, variable block size, motion estimation with quarter-pixel-accuracy, loop filter, etc. The adoption of these tools enables an H.264-coded bitstream to have more information compared with previous standards. In this paper we proposed an effective spatial error concealment method with low complexity. Among the information included in an H.264-coded bitstream, we use prediction modes of intra-blocks for recovering a damaged block. This is because a prediction direction in each prediction mode is highly correlated to the edge direction. We first estimate the edge direction of a damaged block using prediction modes of intra-blocks adjacent to a damaged block and classify the area inside a damaged block into the edge and the flat area. And then our method recovers pixel values in the edge area using edge-directed interpolation, and recovers pixel values in the flat area using weighted interpolation. Simulation results show the proposed method yields better video quality than conventional approaches. [ABSTRACT FROM AUTHOR]

The multi-view simul-switching is one of the most important features of dynamic light field (DLF) streaming. In this paper, we jointly consider light field rendering and compression and propose a novel DLF compression scheme based on the requirements of DLF streaming. In this scheme, successive temporal prediction chains are broken and a shared field is used as a reference for all the later P frames in a group of field. Meanwhile, considering the region of interest for DLF rendering, we partition all the P frames into regional blocks and code them in a manner that any region block can be independently transmitted for bandwidth economized streaming. With this coding scheme, a multi-camera DLF system is developed to verify the streaming performance of the proposed scheme. Experimental results show that our scheme saves the per-user transmission bandwidth a lot compared with other DLF compression schemes. [ABSTRACT FROM AUTHOR]

In this paper, we present a new method to speed up the mode decision process using mode prediction. In general, video coding exploits spatial and temporal redundancies between video blocks, in particular temporal redundancy is a crucial key to compress video sequence with little loss of image quality. The proposed method determines the best coding mode of a given macroblock by predicting the mode and its rate-distortion (RD) cost from neighboring MBs in time and space. Compared to the H.264/AVC reference software, the simulation results show that the proposed method can save up to 53% total encoding time with up to 2.4% bit rate increase at the same PSNR. [ABSTRACT FROM AUTHOR]

It is well known that motion detection using single frame differencing, while computationally much simpler than other techniques, is more liable to generate large areas of false foregrounds known as ghosts. In order to overcome this problem the authors propose a method based on signed differencing and connectivity analysis. The proposal is suitable to applications which cannot afford the un-avoidable errors of background modeling or the limitations of 3-frames preprocessing. [ABSTRACT FROM AUTHOR]

This paper describes a pre-processing for DCT-based coders and more generally for block-based image or video coders taking advantage of the orientation of the blocks. Contrary to most solutions proposed so far, it is not the transform that adapts to the signal but the signal that is pre-processed to fit the transform. The blocks are oriented using circular shifts at the pixel level. Before applying these shifts, the orientation of each block is evaluated with the help of a selection based on a rate-distortion criterion. We show that the insertion of this pre-processing stage in an H.264 coder and applied on residual intra frames can improve its rate-distortion performance. [ABSTRACT FROM AUTHOR]

Employing block-based motion models in scalable video coding based on spatial-domain motion-compensated temporal filtering (SDMCTF) introduces artificial block-boundary discontinuities that adversely affect the video compression performance, particularly at low bit-rates. This paper focuses on the problem of deblocking in the context of SDMCTF-based video coding. One possible solution to this problem is the use of overlapped-block motion compensation (OBMC). An alternative solution is applying an adaptive deblocking filter, similar to the one used in H.264. With this respect, a novel adaptive deblocking filter, tailored to SDMCTF video coding is proposed. In terms of visual-quality, both approaches yield similar performance. However, adaptive deblocking is less complex than OBMC, as it requires up to 34% less processing time. Experimental results show that the two techniques significantly improve the subjective and objective quality of the decoded sequences, confirming the expected benefits brought by deblocking in SDMCTF-based video coding. [ABSTRACT FROM AUTHOR]

This paper presents an approach for evaluating multiple color histograms during object tracking. The method adaptively selects histograms that well distinguish foreground from background. The variance ratio is utilized to measure the separability of object and background and to extract top-ranked discriminative histograms. Experimental results demonstrate how this method adapts to changing appearances of both object undergoing tracking and surrounding background. The advantages and limitations of the particle filter with embedded mechanism of histogram selection are demonstrated in comparisons with the standard CamShift tracker and a combination of CamShift with histogram selection. [ABSTRACT FROM AUTHOR]

Intra coding in current hybrid video coding method has very important functionality like low delay in decoder, random access and error resilience. Unfortunately coding efficiency of intra frame is very low relative to inter frame coding because of mismatch between current block and its predicted block. In this paper, new intra luma prediction algorithm which improves intra coding efficiency is proposed. The proposed additional intra luma prediction mode uses collocated chroma pixels and weight values to estimate correct spatial pattern of coded block. From neighboring blocks, weight value between chroma and luma values is calculated and then the predicted luma block is obtained by multiplying calculated weight value and collocated upsampled chroma block. The proposed method is effective for complex or non-directional macroblocks and experimental results show that the efficiency of intra coding is increased up to 0.6 dB. [ABSTRACT FROM AUTHOR]

Motion estimation by means of spatio-temporal energy filters -velocity tuned filters- is known to be robust to noise and aliasing and to allow an easy treatment of the aperture problem. In this paper we propose a motion representation based on the composition of spatio-temporal energy features, i.e., responses of a set of filters in phase quadrature tuned to different scales and orientations. Complex motion patterns are identified by unsupervised cluster analysis of energy features. The integration criterion reflects the degree of alignment of maxima of the features's amplitude, which is related to phase congruence. The composite-feature representation has been applied to motion segmentation with a geodesic active model both for initialization and image potential definition. We will show that the resulting method is able to handle typical problems, such as partial and total occlusions, large inter-frame displacements, moving background and noise. [ABSTRACT FROM AUTHOR]

Most existing object segmentation algorithms suffer from a so-called under-segmentation problem, where parts of the segmented object are missing and holes often occur inside the object region. This problem becomes even more serious when the object pixels have similar intensity values as that of backgrounds. To resolve the problem, we propose a constrained region-growing and contrast enhancement to recover those missing parts and fill in the holes inside the segmented objects. Our proposed scheme consists of three elements: (i) a simple linear transform for contrast enhancement to enable stronger edge detection; (ii) an 8-connected linking regional filter for noise removal; and (iii) a constrained region-growing for elimination of those internal holes. Our experiments show that the proposed scheme is effective towards revolving the under-segmentation problem, in which a representative existing algorithm with edge-map based segmentation technique is used as our benchmark. [ABSTRACT FROM AUTHOR]

A moving object in a video sequence is removed and corresponding background is completed by using a novel global feature registration technique. To find a 2D homography between two adjacent video frames, we track background and foreground features, separately. After estimating the homography, we extract and remove the moving object in every frame. To fill the background of the removed object accurately, we introduce a global feature registration technique. The technique iteratively reduces and distributes the accumulation errors associated to global video registration. Experimental results show that the proposed technique yields seamless background sequences. [ABSTRACT FROM AUTHOR]

A fast motion estimation (ME) algorithm is proposed to search motion vectors for variable blocks. The proposed method is based on the successive elimination algorithm (SEA) using sum norms to find the best estimate of the motion vectors and to implement efficient calculations for variable blocks. The proposed ME algorithm is applied to the Joint Video Team (JVT) encoder that performs a variable-block ME. In terms of computational complexity, the proposed ME algorithm with limited search range searches motion vectors at about 6.3 times as fast as the spiral full search and 5.5 times as fast as the fast full search using the hierarchical sum of absolute difference (SAD), while the PSNR (peak signal-to-noise ratio) of the reconstructed image is slightly degraded with only 0.1~0.4 dB. [ABSTRACT FROM AUTHOR]

The H.264/AVC standard uses new coding tools to improve coding efficiency. Among the tools, motion estimation using smaller block sizes leads to higher correlation between the motion vectors of neighboring blocks. This characteristic of H.264/AVC is useful for motion vector recovery to conceal a lost macroblock. In this paper, we propose a motion vector recovery method based on optical flow in H.264/AVC video coding. We first determine the optical flow region to alleviate the complexity, and choose an initial value of flow velocity using neighboring motion vectors of a lost macroblock. The proposed method recovers the motion vectors of 4x4 blocks included in a lost macroblock using the weighted average of obtained flow velocities. Simulation results show that our proposed method gives higher objective and subjective visual qualities than conventional approaches. [ABSTRACT FROM AUTHOR]

An approach is presented for characterize objects and image texture by local lacunarity. This measure makes possible to distinguish sets that have same fractal dimension. In image analysis it can be used as a new feature in the pattern recognition process mainly for identification of natural textures. Illustrating the approach, two types of examples were presented: 3D objects representing approximations of fractal sets and medical images. In the first type, we apply this approach to show its possibility when the objects presents the same fractal dimension. The second type shows that it can be used as a feature on pattern recognition alone in many resolutions. [ABSTRACT FROM AUTHOR]

In this paper we present our region merging algorithm that is built with special attention on speed but still includes all the necessary functionality to use a wide range of both region based and border based dissimilarity criteria. The algorithm includes a novel method to dynamically link the common borders between two segments during the region merging. The main part of the paper will concentrate on the efficient data structures and functions that are needed to obtain a fast region merging algorithm. Also, all the special situations that can occur in the segment topology are completely covered. We give a detailed report on the execution times of the algorithm and show some of the segmentation results we obtained. [ABSTRACT FROM AUTHOR]

In general, the less probable an event, the more attention we pay to it. Likewise, considering visual perception, it is interesting to regard important image features as those that most depart from randomness. This statistical approach has recently led to the development of adaptive and parameterless algorithms for image analysis. However, they require computer-intensive statistical measurements. Digital retinas, with their massively parallel and collective computing capababilities, seem adapted to such computational tasks. These principles and opportunities are investigated here through a case study: extracting meaningful segments from an image. [ABSTRACT FROM AUTHOR]

A new design for image processing frameworks is proposed. The new design addresses high-level abstractions suited for component-based image processing applications, in particular real-time image processing with high performance demands. The RIM framework, an implementation of this design, is gone through. It is explained how RIM can be adapted in applications, and integrated with other image libraries. It is also shown how it can be used to confirm some properties of widely used image formats. [ABSTRACT FROM AUTHOR]

Due to the variable block sizes and multi-reference frame used in the H.264/AVC standard; the motion estimation process becomes even more computationally intensive, resulting in a very low encoding speed. To overcome this low encoding speed, fast motion estimation algorithms such as UMHexagonS [1] and EPZS [2] have been proposed. Since the integer-pixel motion estimation speed has significantly decreased, the fractional or sub-pixel motion estimation speed is no longer non-negligible. We propose a fast sub-pixel motion estimation algorithm using an adaptive rood pattern based on the fractional motion vector of adjacent blocks and also a simplified small diamond search. Our algorithm is able to reduce the number of sub-pixel search points by more than 50%, while restricting the PSNR loss to less than 0.1 dB, compared to the hierarchical fractional pixel search. [ABSTRACT FROM AUTHOR]

The use of active contours for texture segmentation seems rather attractive in the recent research, indicating that such methodologies may provide more accurate results. In this paper, a novel model for texture segmentation is presented, combining advantages of the active contour approach with texture information acquired by the Local Binary Pattern (LBP) distribution. The proposed LBP scheme has been formulated in order to capture regional information extracted from distributions of LBP values, characterizing a neighborhood around each pixel, instead of using a single LBP value to characterize each pixel. The log-likelihood statistic is employed as a similarity measure between the LBP distributions, resulting to more detailed and accurate segmentation of texture images. [ABSTRACT FROM AUTHOR]

A new multidimensional modeling of data has recently been introduced, which can be used a wide range of signals. This paper presents multiway filtering for denoising hyperspectral images. This approach is based on a tensorial modeling of the desired information. The optimization criterion used in this multiway filtering is the minimization of the mean square error between the estimated signal and the desired signal. This minimization leads to some estimated n-mode filters which can be considered as the extension of the well-known Wiener filter in a particular mode. An ALS algorithm is proposed to determine each n-mode Wiener filter. Using the ALS loop allows to take into account the mode interdependence. This algorithm requires the signal subspace estimation for each mode. In this study, we have extended the well-know Akaike Information Criterion (AIC) and the minimum description length (MDL) criterion to detect the number of dominant eigenvalues associated with the signal subspace. The performance of this new method is tested on hyperspectral images. Comparative studies with classical bidimensional filtering methods show that our algorithm presents good performances. [ABSTRACT FROM AUTHOR]

Only three set of pattern chain elements to detect corners in irregular shapes are introduced. A code based on three orthogonal change directions, when visiting a contour shape, are used. Previous approaches for detecting corners employ eight different symbols and usually compute angles and maximum curvature. The three basic pattern contour chain elements, founded in this paper, represent changes of direction in the contour curves, requiring few computing power to obtain corners. Also, we have found that the method is independent of shape orientation. Keywords: Shape corner; Contour; Chain element; Freeman chain code; Symbol chain code; Pattern substrings. [ABSTRACT FROM AUTHOR]

Recent developments in dynamic contour tracking in video sequences are based on prediction using dynamical models. The parameters of these models are fixed by learning the dynamics from a training set to represent plausible motions, such as constant velocity or critically damped oscillations. Thus, a problem arise in cases of non-constant velocity and unknown interframe motion, i.e. unlearned motions, and the CONDENSATION algorithm fails to track the dynamic contour. The main contribution of this work is to propose an adaptative dynamical model which parameters are based on non-linear/non-gaussian observation models. We study two different approaches, one statistical and one shape-based, to estimate the deformation of an object and track complex dynamics without learning from a training set neather the dynamical nor the deformation models and under the constraints of missing data, non-linear deformation and unknown interframe motion. The developed approaches have been successfully tested on several sequences. [ABSTRACT FROM AUTHOR]

Image segmentation using graph cuts have become very popular in the last years. These methods are computationally expensive, even with hard constraints (seed pixels). We present a solution that runs in time proportional to the number of pixels. Our method computes an ordered region growing from a set of seeds inside the object, where the propagation order of each pixel is proportional to the cost of an optimum path in the image graph from the seed set to that pixel. Each pixel defines a region which includes it and all pixels with lower propagation order. The boundary of each region is a possible cut boundary, whose cut measure is also computed and assigned to the corresponding pixel on-the-fly. The object is obtained by selecting the pixel with minimum-cut measure and all pixels within its respective cut boundary. Approaches for graph-cut segmentation usually assume that the desired cut is a global minimum. We show that this can be only verified within a reduced search space under certain hard constraints. We present and evaluate our method with three cut measures: normalized cut, mean cut and an energy function. [ABSTRACT FROM AUTHOR]

We propose a novel active contour model by incorporating particle based electrostatic interactions into the geometric active contour framework. The proposed active contour, embedded in level sets, propagates under the joint influence of a boundary attraction force and a boundary competition force. Unlike other contour models, the proposed vector field dynamically adapts by updating itself when a contour reaches a boundary. The model is then more invariant to initialisation and possesses better convergence abilities. Analytical and comparative results are presented on synthetic and real images. [ABSTRACT FROM AUTHOR]

A new evolutionary approach for construction of uniform impulse noise filter is presented. Genetic programming is used for combining the basic image transformations and filters into tree structure, which can accurately estimate noise map. Proposed detector is employed for building switching-scheme filter, where recursively implemented α-trimmed mean is used as the estimator of corrupted pixel values. The proposed evolutionary filtering structure shows very good results in removal of uniform impulse noise, for wide range of noise probabilities and different test images. [ABSTRACT FROM AUTHOR]

In this paper we compare the overall image quality of 7 state-of-the-art denoising schemes, based on human visual perception. A psycho-visual experiment was set up in which 37 subjects were asked to score and compare denoised images. A perceptual space is constructed from this experiment through multidimensional scaling (MDS) techniques using the perceived dissimilarity and quality preference between the images and the scaled perceptual attributes bluriness and artefacts. We found that a two-dimensional perceptual space adequately represents the processed images used in the experiment, and that the perceptual spaces obtained for all scenes are very similar. The interpretation of this space leads to a ranking of the filters in perceived overall image quality. We can show that the impairment vector, whose direction is opposite to that of the quality vector, lies between the attribute vectors for bluriness and artefacts, which on their account form an angle of about 35 degrees meaning they do interact. A follow-up experiment allowed us to determine even further why subjects preferred one filter over the other. [ABSTRACT FROM AUTHOR]

For nonseparable bidimensional wavelet transforms, the choice of the dilation matrix is all-important, since it governs the downsampling and upsampling steps, determines the cosets that give the positions of the filters, and defines the elementary set that gives a tesselation of the plane. We introduce nonseparable bidimensional wavelets, and give formulae for the analysis and synthesis of images. We analyze several dilation matrices, and show how the wavelet transform operates visually. We also show some distorsions produced by some of these matrices. We show that the requirement of their eigenvalues being greater than 1 in absolute value is not enough to guarantee their suitability for image processing applications, and discuss other conditions. Keywords: quincunx, nonseparable, dilation, wavelet. [ABSTRACT FROM AUTHOR]