中文摘要：

构建了一种基于离散余弦变换（discrete cosine transform,DCT）域采样和超分辨率（super resolution,SR）重建的低码率图像压缩编码算法。在编码端对原始图像进行分块离散余弦变换（DCT）,并提取每个DCT系数块的低频系数,然后再反变换到空间域,从而得到在DCT域下采样的低分辨率（low resolution,LR）图像块。用JPEG标准对下采样图像块编解码后,采用基于学习的方法恢复DCT域高频系数,重建出高分辨率（high resolution,HR）的图像。实验结果表明,在码率较低的情况下,算法比JPEG编码标准具有更好的率失真性能;同时,在相同码率下,算法重建的解码图像视觉效果更好。

英文摘要：

An image Compression algorithm is presented via combining the discrete cosine transformation （DCT） domain down-sampling and super-resolution reconstruction. Firstly, the image is first divided into non-over- lapping blocks, and each block is transformed by DCT. Secondly, low frequency coefficients of each block are ex- tracted and inverse-transformed to generate the down-sampled low resolution image. After the down-sampled image is compressed and decompressed by the standard JPEG. the high freauencv coefficients are recovered by the learn-ing-based method in the spatial domain. Experimental results show that the compression algorithm presented has better rate-distortion performance than JPEG at low bit rate, and the visual quality of decompressed image by our method is also better at the same coding bit rate.