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Vector quantization (VQ) is a commonly used technique for image compression. Typically, the common codebooks (CCBs) that are designed by using multiple training images are used in VQ. The CCBs are stored in the public websites such that their storage cost can be omitted. In addition to the CCBs, the private codebooks (PCBs) that are designed by using the image to be compressed can be used in VQ. However, calculating the bit rates (BRs) of VQ includes the storage cost of the PCBs. It is observed that some codewords in the CCB are not used in VQ. The codebook refinement process is designed to generate the refined codebook (RCB) based on the CCB of each image. To cut down the BRs, the lossless index coding process and the two-stage lossless coding process are employed to encode the index table and the RCB, respectively. Experimental results reveal that the proposed scheme (PS) achieves better image qualities than VQ with the CCBs. In addition, the PS requires less BRs than VQ with the PCBs.

Two color image coding schemes based on single bit map block truncation coding are proposed in this paper. The first scheme employs the optimal rule for single bit map generation. In addition, the quantization level recomputation process is designed. By using these two techniques, a fixed bit rate image coding scheme is introduced. To further cut down the required bit rates of the first scheme, the similar block prediction technique and the bit map omission technique are employed in the second scheme. According to the experimental results, the first scheme proposed significantly improves the image qualities of the compressed images compared to the traditional single bit map block truncation coding scheme. In addition, good image qualities of the compressed images are achieved by the second scheme while keeping bit rates low.

A tamper detection method to protect the integrity of indexed color images is presented. This method generates authentication codes of the indices based on the pseudorandom number generator. The length of authentication codes can be adaptively chosen according to the user’s requirement. The authentication codes are embedded into the index table of the indexed color image. In the tamper detection procedure, the embedded authentication codes are extracted. Besides, the pseudorandom number generator with the specific random seed is used to generate another set of authentication codes. By means of comparing the two sets of authentication codes, the tampered areas of the indexed color images can be found. Experimental results show that the proposed method efficiently detects the tampered areas while keeping good image qualities of embedded images.

A joint image coding and image authentication scheme based on absolute moment block truncation coding (AMBTC) is pro- posed. In the proposed scheme, the authentication data is generated by using the pseudo random sequence. Then, the authentication codes are embedded into the bit maps of AMBTC-compressed image blocks. The embedded bit maps and these quantization levels are further losslessly compressed to cut down the required storage cost. Experimental results demonstrate that the proposed scheme achieves good image quality of the embedded image while keeping good detecting accuracy. © 2013 SPIE and IS&T (DOI: 10.1117/1.JEI .22.1.013012)

We propose a fast palette design scheme based on the K-means algorithm for color image quantization. To accelerate the K-means algorithm for palette design, the use of stable flags for palette entries is introduced. If the squared Euclidean distances incurred by the same palette entry in two successive rounds are quite similar, the palette entry is classified to be stable. The clustering process will not work on these stable palette entries to cut down the required computational cost. The experimental results reveal that the proposed algorithm consumes a lower computational cost than those comparative schemes while keeping approximately the same image quality.

A new image hiding scheme is proposed that can embed color secret images into color host images. The secret image to be embedded is first color quantized using a palette previously sorted by the principal component analysis technique to generate the indexed color image. Then the concept of pixel difference is employed to process both the host image and the indexed color image. Then the difference image of the indexed color image is embedded into the difference image of the color host image. According to our experimental results, the image quality of the stegoimage is quite good when our new method is used to embed a color secret image into the color host image.

In this paper, a novel image compression scheme based on the moment preserving block truncation coding (MPBTC) scheme is proposed. In this scheme, three techniques are employed to cut down the bit rate of moment preserving block truncation cod- ing. They are the two-dimensional prediction technique, the bit map omission technique, and the bit map coding using edge patterns. According to the experimental results, the proposed scheme not only achieves good image quality at low bit rate, but also requires little computational cost in the encoding/decoding procedures. In other words, the proposed scheme indeed improves the perfor- mance of the MPBTC scheme and it is quite suitable for those mul- timedia applications with low computational cost requirement.

A novel image compression scheme based on absolute moment block truncation coding (AMBTC) is proposed. The quadtree segmentation technique is employed in this scheme to exploit the variable-block-sized segmentation. In addition, the concept of using visual patterns to reduce the storage cost of the BTC bit plane is incorporated into this scheme. Finally, the bit plane omission technique is employed if these two quantization levels in each image block are quite similar. According to the experimental results, it is shown that the proposed scheme requires very little computational complexity. Besides, a good image quality of the compressed image can be obtained while the required bit rate is relatively low. In other words, the proposed scheme indeed provides a good approach to compress digital images with little computational cost at a low bit rate.

A novel variable-rate image-coding scheme called the predictive subcodebook search algorithm (PSS) is proposed. In PSS, the initial searched codeword for each input vector is predicted by its encoded neighbors and the closest codeword in the codebook is searched from a specific range (or subcodebook) that is determined dynamically according to the block type of its encoded neighbors. In addition, the relative addressing technique is employed to encode the searched closest codeword. According to the simulation results, it is shown that PSS not only provides better objective image quality peak SNR (PSNR) but also reduces the storage cost for storing multiple codebooks. Furthermore, PSS requires very little computational cost, compared to the full search algorithm for the vector quantization (VQ) scheme. Therefore, it is concluded that PSS indeed provides a good means for variable-rate image coding.

Vector quantization (VQ) and block truncation coding (BTC) are two popular schemes for image compression. VQ has been widely used for its simplicity and low bit rate; on the other hand, BTC has the advantages of requiring little computational cost and providing high image quality. To put together the advantages of VQ and BTC, three hybrid methods based on VQ and BTC are proposed in this paper. According to our experimental results, it is shown that the first two methods of ours produce good image quality while keeping low bit rate. Meanwhile, the third method produces higher image quality while keeping acceptable bit rate. Also, these methods require little computational cost. In other words, our methods can be applied to diverse occasions according to their specific requirements.