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Without demosaicing processing, this paper first proposes a new approach to extract more accurate gradient/edge information on mosaic images directly. Next, based on spectral-spatial correlation, a novel adaptive heterogeneity-projection with proper mask size for each pixel is presented. Combining the extracted gradient/edge information and the adaptive heterogeneity-projection values, a new edge-sensing demosaicing algorithm is presented. Based on 24 popular testing images, experimental results demonstrated that our proposed high-quality demosaicing algorithm has the best image quality performance when compared with several recently published algorithms.

Recently, a fast spatial combinative lifting algorithm (SCLA) for performing the wavelet transform (WT) was presented by Meng and Wang, and the SCLA speeds up the well-known lifting scheme presented by Daubechies and Sweldens. Employing the concept in the block-based WT by Bao and Kuo, this letter presents an efficient cache-based SCLA (CSCLA) for performing the WT. Theoretically, the number of total arithmetical operations required in the proposed CSCLA is equal to that in the SCLA. Experimental results confirm the computational advantage of our proposed CSCLA when compared to some other previous results. In addition, the VTune Performance Analyzer is used to evaluate the cache performance among the concerning algorithms. [Copyright &y& Elsevier]

Given a polygonal curve P in three-dimensional (3-D) space, the polygonal approximation (PA) problem in this research is to find a polygon P′ to approximate P either with the minimal polygonal segments under a given error or, conversely, with the minimal error under a specified number of segments allowable. The former PA problem is called the PA-# problem; the latter PA problem is called the PA-ϵ problem. Given a 3-D P with n nodes, under the local integral square error criterion, this paper first presents an O(n2)-time algorithm for solving the PA-# problem using O(n) space. Then we present an O(n2 log n)-time algorithm for solving the PA-ϵ using O(n2) space. Finally, a sampling technique is employed to reduce the memory requirement from O(n2) to O(n). Some experiments are carried out to confirm the theoretical analysis. [Copyright &y& Elsevier]

Abstract: In this paper, a new and efficient edge-preserving algorithm is presented for color contrast enhancement in CIE color space. The proposed algorithm not only can enhance the color contrast as the previous algorithm does, but also has an edge-preservation effect. In addition, the spurious edge points occurred due to the color contrast enhancement can be well reduced using the proposed algorithm. This is the first edge-preserving algorithm for color contrast enhancement in color space. Furthermore, a novel color image segmentation algorithm is presented to justify the edge-preservation benefit of the proposed color contrast enhancement algorithm. Based on some real images, experimental results demonstrate the advantages of color contrast enhancement, edge-preservation effect, and segmentation result in our proposed algorithm. [Copyright &y& Elsevier]

The slope-intercept Hough transform (SIHT) is one of the two types of line-detection methods. However, the disadvantage of the SIHT is its low memory utilization, say 50%. Based on the affine transformation, this paper presents a new method to improve the memory utilization of the SIHT from 50% to 100%. According to the proposed affine transformation, we first present a basic SIHT-based algorithm for detecting lines. Instead of concerning floating-point operations in the basic SIHT-based algorithm, an improved SIHT-based algorithm, which mainly concerns integer operations, is presented. Besides the memory utilization advantage, experimental results reveal that the improved SIHT-based algorithm has more than 60% execution time improvement ratio when compared to the basic SIHT-based algorithm and has more than 33% execution time improvement ratio when compared to another type of line-detection methods, such as the (r,θ)-based HT algorithm and its variant. The detailed complexity analyses for all the related algorithms are also investigated and we show that the time complexity required in the improved SIHT-based algorithm is the least. [Copyright &y& Elsevier]