Abstract
Problem statement: Efficient color image compression algorithm is essential for mass storage and the transmission of the image. The compression efficiency of the Set Partitioning in Hierarchical Tree (SPIHT) coding algorithm for color images is improved by using correlation theory. Approach: In this study the correlation between the color channels are used to propose the new algorithm. The correlation between the color channels are analyzed in various color spaces and the color space CIE-UVW in which the color channels are highly correlated is taken. The most correlated U channel is considered as base color and compressed by using the wavelet filter and the SPIHT algorithm. The linear approximation of the two of the color components (V and W) based on the primary color component U is used to code subordinate color components. The image is divided into N*N blocks in each color channels. The linear approximation coefficients are calculated for each block of the subordinate colors V and W as functions of the base color. Only these coefficients of each block are coded and send to the receiver along with the SPIHT coding of the base color. Results: By using this algorithm, a significant (4 dB mean value) Peak Signal to Noise Ratio (PSNR) improvement is obtained compared to the traditional coding scheme for the same compression rate and reduces the coding and decoding time. Also the proposed compression algorithm reduces the complexity in coding and decoding algorithms. Conclusion: This algorithm allows the reduction of complexity for both coding and decoding of color images. It is concluded that a significant PSNR gain and visual quality improvement is obtained. It is found that in color image coding, this algorithm is superior to the traditional de-correlation based methods and reduces the coding and decoding time.
Highlights
The uncompressed image data requires a large storage capacity and transmission bandwidth
The Discrete Cosine Transform (DCT) and wavelet transform are commonly used to reduce the redundancy between the pixels and for energy compaction
In the traditional color image compression algorithm the redundancy between the color channels are reduced by transforming them into a de-correlated color space such as YCbCr, YPbPr, YIQ, YUV
Summary
The uncompressed image data requires a large storage capacity and transmission bandwidth. Correlation exists between the neighboring pixels of each color channel and as well as between the color channels (San, 2006). In the traditional color image compression algorithm the redundancy between the color channels are reduced by transforming them into a de-correlated color space such as YCbCr, YPbPr, YIQ, YUV. The linear approximation coefficients are needed to represent the data set. The linear approximation coefficients are calculated for each block of the subordinate colors V and W as functions of the base color. These coefficients of each block are coded and send to the receiver along with the SPIHT coding of the base color. The performance of the proposed algorithm and the traditional color SPIHT are compared in this study and it is found that correlation based SPIHT algorithm is superior to the traditional decorrelation based SPIHT algorithm
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