Adaptive image compression system based on TMS320C6713

Abstract

A novel adaptive real-time image compression framework based on TMS320C6713 is presented in this paper. Via analyzing image texture, different compression ratio is applied for reducing the code stream. Owing to its low-cost, highspeed and low power performances, C6713 is selected as the main processor of framework. Firstly, the original image is transformed through lifting wavelet transform algorithm. Then, the resultant transformed data is encoded with zero tree wavelet, thereby completing the compression of 320x256 image with input bandwidth 2.34MB/s and output bandwidth 100kB/s. Moreover, the experimental results demonstrate that the adaptive image ratio can reach 25:1 with PSNR 30 and frame frequency can achieve 25fps with a high-speed processor.

Medical image compression framework based on compressive sensing, DCT and DWT

“…In [3][4][5][6][7][8][9][10] authors have used the above mentioned, concept of compressive sensing for compressing the medical images like CT, MRI etc. using various transforms.In this paper, we implemented the medical images-CT and MRI-compression using DCT, DWT and CS.The compression performance is evaluated using parameters like peak signal to noise ratio (PSNR), root mean square error (RMS) and correlation coefficient (CoC).…”