A novel lossless compression for hyperspectral images by context-based adaptive classified arithmetic coding in wavelet domain

作者：Zhang Jing^*; Liu Guizhong

来源：IEEE Geoscience and Remote Sensing Letters, 2007, 4(3): 461-465.

DOI：10.1109/LGRS.2007.897924

• context-based adaptive classified arithmetic coding
• hyperspectral images
• lifting integer wavelet transforms

A novel hyperspectral-image lossless compression scheme in the wavelet domain is proposed in this letter. This scheme is based on the context-based adaptive classified arithmetic-coding technique. The adaptive classified scheme divides each of the residual images between the two adjacent wavelet images into different classes, resulting in not only skipping the coding of a lot of insignificant zeros but also making the similar coefficients cluster together. Through experiments, we found that, when similar coefficients are clustered together, the arithmetic coding can achieve a higher performance than no clustering. Therefore, we can say that the adaptive classified scheme makes a better use of the characteristics of hyperspectral images and the characteristics of the arithmetic-coding technique. Experiments show that our proposed scheme is capable of providing high compression performance.

• 出版日期2007-7
• 单位西安交通大学