The CA-CMAC for downsampling image data size in the compressive domain

The CA-CMAC for downsampling image data size in the compressive domain is proposed in this paper. When the transmitting data is limited, it can reduce the bit rate during transmitting image data and decrease computations per pixel during the reconstructive process. The proposed method maps the image data into the CMAC lookup table, which can learn the characteristics of original image and can change image data size during downsampling and upsampling processes. It is unlike the conventional linear interpolation method, which gets lower SNR and costs more computation in the compression and reconstructive processes. The CA-CMAC method uses only a few hypercubes to learn the characteristics of original image, and transmits the learned characteristics to the receiver for reconstruction. Finally, the proposed method is applied to downsample JPEG data size in this paper, and it is shown that it gets high SNR after reconstruction.