Blockwise distortion measure for lossy compression of multispectral images

A new blockwise distortion measure is proposed to evaluate the quality of lossy compressed multispectral images. The measure is based on blockwise distortions which are calculated between the original multispectral image and the compressed/reconstructed multispectral image. The calculated measures with various compression ratios are matched to a visual scale which is based on the mean opinion score (MOS). The nonlinear weighting using neural network is used for matching. The results from the new measure are compared to mean-square-error (MSE) based measures, to two-dimensional blockwise distortion measure, and to picture quality scale for grayscale images. The multispectral images are compressed using multiwavelets, principal component analysis, and DCT/JPEG.