A class-specified learning based super resolution for low-bit-rate compressed images

Han Zhao, Xiaoguang Li, L. Zhuo
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引用次数: 1

Abstract

Due to limitations on the image capturing devices, distance, storage capability and bandwidth for transmission, many images in multimedia applications are low-bit-rate compressed and low resolution. In this paper, we proposed a class-specified learning based super resolution for this kind of low quality images. Firstly, we proposed a class-specified filter to remove the compressed distortions. Then a class-specified learning based scheme is employed to super resolve images with different compression rates. Experimental results show that the proposed method can improve both the objective and subjective quality of the images effectively.
基于类指定学习的低比特率压缩图像的超分辨率
由于图像采集设备、距离、存储能力和传输带宽的限制,多媒体应用中的许多图像都是低比特率压缩和低分辨率的。本文针对这类低质量图像,提出了一种基于类指定学习的超分辨率算法。首先,我们提出了一个类指定滤波器来去除压缩失真。然后采用一种基于类指定学习的方案对不同压缩率的图像进行超分辨。实验结果表明,该方法能有效地提高图像的主客观质量。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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