基于消除空间冗余和图像修复的图像压缩技术

本文介绍了一种基于图像修复方法的图像压缩算法。首先对能够被精确覆盖的图像区域进行定位;然后将这些区域的信息消除以减少数据量;除了用于恢复被消除区域必要细节的数据外,对其余的数据进行编码以产生输出数据。在解码器中,使用从编码器中提取的信息可以重新获得被消除的图像区域。该修复技术利用偏微分方程（PDE）进行图像信息收集,其目的是达到图像压缩标准中的较高质量。本文还针对各种图像开展该算法的研究。采用这种算法,在图像质量可接受的条件下,压缩比可高达1：40。实验结果表明,与JPEG压缩方法相比,该算法在高压缩比下图像质量明显提高。

Image Compression Based on Spatial Redundancy Removal and Image Inpainting

We present an algorithm for image compression based on an image inpainting method.First the image regions that can be accurately recovered are located.Then,to reduce the data,information of such regions is removed.The remaining data besides essential details for recovering the removed regions are encoded to produce output data.At the decoder,an inpainting method is applied to retrieve removed regions using information extracted at the encoder.The image inpainting technique utilizes partial differential equations（PDEs）for recovering information.It is designed to achieve high performance in terms of image compression criteria.This algorithm was examined for various images.A high compression ratio of 1：40 was achieved at an acceptable quality.Experimental results showed attainable visible quality improvement at a high compression ratio compared with JPEG.