Image Decoding Method Based on Sparse Representation Model

To obtain the sparse property of signals better,a mliti-directional adaptive sparse model and recovery algorithm for it in compressive sensing were proposed.The mliti-directional autoregressive model could use the local statistical correlation and texture directions of image to represent signal sparsely.In a transform based codec framework,the transform matrix was regarded as a measurement matrix.The traditional inverse transform in decoder is replaced by the multidirectional adaptive sparse model.Simulation results over a wide range of images show that the proposed technique can improve the reconstruction quality of JPEG.