Wavelet-Based SPIHT Encoding

Wavelet-based SPIHT encoding is an image compression algorithm that combines wavelet transform with sorting encoding techniques to compress image data. SPIHT stands for "Set Partitioning in Hierarchical Trees," where the algorithm partitions image data into different subsets and encodes each subset separately to achieve efficient image compression. The MATLAB implementation typically involves three key components: wavelet decomposition using functions like wavedec2(), SPIHT sorting pass that organizes coefficients based on significance thresholds, and refinement pass that progressively improves bitplane accuracy. The algorithm maintains three ordered lists - LIP (List of Insignificant Pixels), LIS (List of Insignificant Sets), and LIS (List of Significant Pixels) - to efficiently track coefficient significance across multiple decomposition levels. SPIHT algorithm is widely used in image compression applications and can be implemented in MATLAB programs through iterative threshold reduction and bitplane coding procedures that prioritize significant coefficients before processing finer details.