Discrete cosine transform: algorithms, advantages, applications
Discrete cosine transform: algorithms, advantages, applications
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
On color transforms and bit allocation for optimal subband image compression
Image Communication
Color image coding using regional correlation of primary colors
Image and Vision Computing
Does decorrelation really improve color image compression?
ISTASC'05 Proceedings of the 5th WSEAS/IASME International Conference on Systems Theory and Scientific Computation
Data compression of color images using a probabilistic linear transform approach
NMA'06 Proceedings of the 6th international conference on Numerical methods and applications
IEEE Transactions on Signal Processing
The JPEG still picture compression standard
IEEE Transactions on Consumer Electronics
A mathematical analysis of the DCT coefficient distributions for images
IEEE Transactions on Image Processing
New correlation analysis method for nonstationary signal
WSEAS Transactions on Information Science and Applications
On texture and image interpolation using Markov models
Image Communication
High-fidelity RGB video coding using adaptive inter-plane weighted prediction
IEEE Transactions on Circuits and Systems for Video Technology
Colour image coding with matching pursuit in the spatio-frequency domain
ICIAP'11 Proceedings of the 16th international conference on Image analysis and processing: Part I
Novel adaptive color space transform and application to image compression
Image Communication
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Most coding techniques for color image compression employ a de-correlation approach-the RGB primaries are transformed into a de-correlated color space, such as YUV or YCbCr, then the de-correlated color components are encoded separately. Examples of this approach are the JPEG and JPEG2000 image compression standards. A different method, of a correlation-based approach (CBA), is presented in this paper. Instead of de-correlating the color primaries, we employ the existing inter-color correlation to approximate two of the components as a parametric function of the third one, called the base component. We then propose to encode the parameters of the approximation function and part of the approximation errors. We use the DCT (discrete cosine transform) block transform to enhance the algorithm's performance. Thus the approximation of two of the color components based on the third color is performed for each DCT subband separately. We use the rate-distortion theory of subband transform coders to optimize the algorithm's bits allocation for each subband and to find the optimal color components transform to be applied prior to coding. This pre-processing stage is similar to the use of the RGB to YUV transform in JPEG and may further enhance the algorithm's performance. We introduce and compare two versions of the new algorithm and show that by using a Laplacian probability model for the DCT coefficients as well as down-sampling the subordinate colors, the compression results are further improved. Simulation results are provided showing that the new CBA algorithms are superior to presently available algorithms based on the common de-correlation approach, such as JPEG.