Layered scalable coding of multispectral images based on visible component separation

This paper presents multispectral image coding methods based on visible component separation techniques. By coding the visible components separately from other spectral components, the color information can be used without decoding the whole multispectral image. Two types of separation techniques are introduced: one is a direct separation of visible and invisible layers, while the other is a scalable separation. In the scalable separation, visible components are first compressed to produce the base layer bitstream. The enhancement layer data include not only invisible components but also the information on the distortion of the coded visible components. Such a separation technique improves the accuracy of decoded multispectral images especially when visible components are highly compressed. The performance of the proposed methods was evaluated for different bit allocations to visible components. In general, the coding performance reduces when data are divided and coded separately to incorporate scalabilities. Nonetheless, it is found that the proposed scalable approach realizes a peak signal-to-noise ratio PSNR value comparable to that achieved by employing JPEG2000, which incorporates no scalability.