Digital Case Image Compression Algorithm based on Deep Learning

The result of deep learning lies in the acquisition of learners' depth of knowledge, which is mainly reflected in the development of higher-order thinking ability and the achievement of higher-order cognitive goals. With the vigorous development of deep learning, people begin to try to use deep learning technology to break through the bottleneck of traditional image compression methods. Based on previous research results, this paper constructs a digital case image compression algorithm model based on deep learning, focusing on network training, quantization module and compression process. The mathematical formula of quality evaluation index of digital case image compression algorithm is derived, including PSNR, SSIM and MS-SSIM. JEPG algorithm and deep learning algorithm are compared and analyzed to illustrate the advantages of deep learning algorithm in the field of image compression. The experimental results show that the deep learning algorithm has obvious advantages in both subjective and objective evaluation.