High-Performance Image Compression Using SPIHT Algorithm

The most recent MATLAB implementation of the SPIHT algorithm achieves high-performance image compression through sophisticated signal processing methods. This algorithm employs advanced wavelet transformations to decompose images into hierarchical subbands, followed by efficient coding of significant coefficients across bit planes. Through pixel-by-pixel analysis and processing, the algorithm utilizes three organized lists (LIP, LIS, and LSP) to track significant coefficients while implementing progressive bitstream transmission. The implementation features threshold-based significance testing and spatial orientation tree structures to preserve image correlation, significantly reducing file size while maintaining image clarity and detail resolution. This innovative approach represents a breakthrough in image compression technology, offering users superior compression efficiency through MATLAB's optimized matrix operations and wavelet processing functions like wavedec2 and waverec2 for multi-level decomposition and reconstruction.