Improved Class-Based Coding of Multispectral Images With Shape-Adaptive Wavelet Transform

Marco Cagnazzo, Sara Parrilli, Giovanni Poggi, Luisa Verdoliva

Abstract: In this letter, we improve the class-based transform-coding scheme proposed by Gelli and Poggi for the compression of multispectral images. The original spatial-coding tools, 1-D discrete cosine transform and scalar quantization, are replaced by shape-adaptive wavelet transform and set partitioning in hierarchical trees. Numerical experiments show that the improved technique outperforms the original one for medium- to high-quality compression and is consistently superior to all reference techniques.