Image Reconstruction Using a Modified Sparse Coding Technique

A novel image reconstruction method for natural images using a modified sparse coding (SC) algorithm is proposed by us. This SC algorithm exploited the maximum Kurtosis as the maximizing sparse measure criterion, and a fixed variance term of sparse coefficients is used to yield a fixed information capacity. The experimental results show that using our algorithm, the natural images' feature basis vectors can be successfully extracted. Furthermore, compared with the standard SC method, the experimental results show that our algorithm is indeed efficient and effective in performing image reconstruction task.