Vector quantization and signal compression
Vector quantization and signal compression
JPEG 2000: Image Compression Fundamentals, Standards and Practice
JPEG 2000: Image Compression Fundamentals, Standards and Practice
ICPR '00 Proceedings of the International Conference on Pattern Recognition - Volume 3
Discrete Cosine Transform: Algorithms, Advantages, Applications
Discrete Cosine Transform: Algorithms, Advantages, Applications
Does decorrelation really improve color image compression?
ISTASC'05 Proceedings of the 5th WSEAS/IASME International Conference on Systems Theory and Scientific Computation
Analysis of low bit rate image transform coding
IEEE Transactions on Signal Processing
IEEE Transactions on Signal Processing
Embedded image coding using zerotrees of wavelet coefficients
IEEE Transactions on Signal Processing
The JPEG still picture compression standard
IEEE Transactions on Consumer Electronics
Context-based entropy coding of block transform coefficients for image compression
IEEE Transactions on Image Processing
Correlation-based approach to color image compression
Image Communication
Color in image and video processing: most recent trends and future research directions
Journal on Image and Video Processing - Color in Image and Video Processing
Optimal color spaces for image demosaicing
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
Novel adaptive color space transform and application to image compression
Image Communication
The optimized wavelet filters for speech compression
International Journal of Speech Technology
| Hi-index | 0.00 |
Although subband transform coding is a useful approach to image compression and communication, the performance of this method has not been analyzed so far for color images, especially when the selection of color components is considered. Obviously, the RGB components are not suitable for such a compression method due to their high inter-color correlation. On the other hand, the common selection of YUV or YIQ is rather arbitrary and in most cases not optimal. In this work we introduce a rate-distortion model for color image compression and employ it to find the optimal color components and optimal bit allocation (optimal rates) for the compression. We show that the DCT (discrete cosine transform) can be used to transform the RGB components into an efficient set of color components suitable for subband coding. The optimal rates can be also used to design adaptive quantization tables in the coding stage with results superior to fixed quantization tables. Based on the presented results, our conclusion is that the new approach can improve presently available methods for color image compression and communication.