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首页> 外文期刊>IEEE Transactions on Geoscience and Remote Sensing >A Novel Vision-Based Adaptive Scanning for the Compression of Remote Sensing Images
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A Novel Vision-Based Adaptive Scanning for the Compression of Remote Sensing Images

机译：一种基于视觉的新型自适应扫描压缩遥感图像

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摘要

Most of the compression methods for remote sensing images are often designed under the guidance of mean square error. However, for the vision-related applications, high peak-signal-to-noise ratio (PSNR) does not mean good visual quality. On the other hand, existing compression methods that considering the human visual system (HVS) are usually designed for natural images, without taking the unique characteristics of remote sensing images into account. Focusing on this problem, we present a novel HVS-based adaptive scanning (HAS) scheme for the compression of remote sensing images. First, after the wavelet transform, a retina-based visual sensitivity model is established, and then, the visual weighting mask is generated. Second, for the weighted transformed image, an adaptive scanning method is proposed, which provides different scanning orders among subbands and within a subband, respectively. The former focuses on organizing the codestream according to the importance of weighted subbands, and the latter aims at preserving the direction information of an image as much as possible. Finally, the binary tree codec is utilized. Experimental results show that, as compared with other scan-based compression methods, the proposed HAS-based compression method can provide better visual quality, which makes it more desirable in vision-related applications for remote sensing images.
机译：大多数遥感图像的压缩方法通常是在均方误差的指导下设计的。但是，对于与视觉相关的应用，高峰值信噪比（PSNR）并不意味着良好的视觉质量。另一方面，考虑到人类视觉系统（HVS）的现有压缩方法通常是为自然图像设计的，而没有考虑遥感图像的独特特征。针对此问题，我们提出了一种新颖的基于HVS的自适应扫描（HAS）方案，用于压缩遥感图像。首先，在小波变换之后，建立基于视网膜的视觉敏感度模型，然后生成视觉加权蒙版。其次，针对加权后的变换图像，提出了一种自适应扫描方法，该方法分别在子带之间和子带内提供不同的扫描顺序。前者专注于根据加权子带的重要性来组织码流，而后者旨在尽可能保留图像的方向信息。最后，利用二叉树编解码器。实验结果表明，与其他基于扫描的压缩方法相比，该基于HAS的压缩方法可提供更好的视觉质量，这使其在与视觉相关的遥感图像应用中更为理想。

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