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A new image reconstruction method using the WTA- ICA model in contourlet transform domain is discussed in this paper. WTA-ICA is in fact an sparse ICA algorithm, and is simpler and faster under high dimensional computational requirements. Contourlet transform can offer a flexible multi- resolution and directional decomposition for images and embody well image structure. Here, for a given image, the contourlet transform is first used to obtain low and high frequency sub-band images at two layers, where each layer behaves four directions. Then, WTA-ICA model is used in contourlet domain to extract low frequency sub-band image features and each layer's high frequency sub-band image features. Further, considered the fusion technique between each layer's high frequency sub-band features, as well as that between the fused high frequency sub-band image features and the first level's low frequency features, the total image fused features can be obtained. Using this fusion feature, an image can be reconstructed well. The quality of reconstructed images is measured by SNR criterion, and compared with WTA-ICA model, the experimental results shown that our method is indeed efficient in image reconstruction task.

Image Reconstruction Using WTA-ICA Model in Contourlet Transform Domain