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Measurement of Texture Loss for JPEG 2000 Compression

机译:JPEG 2000压缩的纹理损失的测量

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The capture and retention of image detail are important characteristics for system design and subsystem selection. An established imaging performance measure that is well suited to certain sources of detail loss, such as optical focus and motion blur, is the Modulation Transfer Function (MTF). Recently we have seen the development of image quality methods aimed at more adaptive operations, such as noise cleaning and adaptive digital filtering. An example of this is the measure of texture (image detail) loss using sets of overlapping small objects, known as dead leaves targets. In this paper we investigate the application of the above method to image compression. We apply several levels of JPEG and JPEG 2000 compression to digital images that include scene content that is amenable to the texture loss measure. A modified form of the method was used. This allowed direct target compensation without data smoothing. Following a camera simulation, the texture MTF and acutance were computed. The standard deviation of the acutance measure was 0.014 (relative error of 1.63%), found by replicate measurements. Structured similarity index (SSIM) values, used for still and video image quality evaluation, were also computed for the image sets. The acutance and SSI results were similar; however the relationship between the two showed an offset between the JPEG and JPEG 2000 images sets.
机译:图像细节的捕获和保留是系统设计和子系统选择的重要特征。调制传递函数(MTF)是一种非常适合某些细节损失源(如光学焦点和运动模糊)的既定成像性能指标。最近,我们看到了针对更自适应操作的图像质量方法的发展,例如噪声清除和自适应数字滤波。这方面的一个示例是使用一组重叠的小物体(称为死叶目标)测量纹理(图像细节)损失的方法。在本文中,我们研究了上述方法在图像压缩中的应用。我们对数字图像应用了几种级别的JPEG和JPEG 2000压缩,这些数字图像包括适合纹理损失度量的场景内容。使用该方法的修改形式。这允许直接目标补偿,而无需数据平滑。在摄像机模拟之后,计算了纹理的MTF和清晰度。通过重复测量发现,冲动测量的标准偏差为0.014(相对误差为1.63%)。还为图像集计算了用于静止和视频图像质量评估的结构相似指数(SSIM)值。攻击和SSI结果相似;但是,两者之间的关系显示了JPEG和JPEG 2000图像集之间的偏移。

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