Classic Algorithm for Image Coding Based on Wavelet Transform

The classic algorithm for image coding using wavelet transform represents a widely adopted methodology. This algorithm encompasses both image compression and decompression procedures, accompanied by executable sample code implementations. By employing this technique, image files can be stored and transmitted with significantly improved efficiency. Wavelet transform serves as a mathematical approach that decomposes images into subbands of different frequencies, enabling effective image compression through thresholding and quantization of wavelet coefficients. During decompression, the original image can be reconstructed while maintaining high visual quality through inverse wavelet transforms and proper coefficient handling. The implementation typically involves key functions for wavelet decomposition (like dwt2 in MATLAB), coefficient thresholding, entropy coding, and reconstruction using inverse transforms (idwt2). Consequently, wavelet transform-based image coding stands as a crucial technology with broad applications in image processing and communication systems, particularly noted for its multiresolution analysis capabilities and energy compaction properties.