基于块的图像压缩与参数辅助修复。

Block-based image compression with parameter-assistant inpainting.

出版信息

IEEE Trans Image Process. 2010 Jun;19(6):1651-7. doi: 10.1109/TIP.2010.2044960. Epub 2010 Mar 8.

DOI:10.1109/TIP.2010.2044960

PMID:20215076

Abstract

This correspondence presents an image compression approach that integrates our proposed parameter-assistant inpainting (PAI) to exploit visual redundancy in color images. In this scheme, we study different distributions of image regions and represent them with a model class. Based on that, an input image at the encoder side is divided into featured and non-featured regions at block level. The featured blocks fitting the predefined model class are coded by a few parameters, whereas the non-featured blocks are coded traditionally. At the decoder side, the featured regions are restored through PAI relying on both delivered parameters and surrounding information. Experimental results show that our method outperforms JPEG in featured regions by an average bit-rate saving of 76% at similar perceptual quality levels.

摘要

这封信件介绍了一种图像压缩方法，该方法集成了我们提出的参数辅助修复（PAI），以利用彩色图像中的视觉冗余。在该方案中，我们研究了不同的图像区域分布，并使用模型类来表示它们。在此基础上，在编码器端，将输入图像按块级划分为特征区域和非特征区域。与预定义模型类匹配的特征块由几个参数进行编码，而非特征块则采用传统方式进行编码。在解码器端，通过 PAI 利用传递的参数和周围信息来恢复特征区域。实验结果表明，在相似的感知质量水平下，与 JPEG 相比，我们的方法在特征区域的平均比特率节省了 76%。