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首页> 外文会议>Computational Imaging V; Proceedings of SPIE-The International Society for Optical Engineering; vol.6498; Electronic Imaging Science and Technology >Compression of noisy Bayer pattern Color Filter Array images
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Compression of noisy Bayer pattern Color Filter Array images

机译：嘈杂的Bayer图案滤色镜阵列图像的压缩

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Bayer Pattern Color Filter Arrays (CFAs) are widely used in digital photo and video cameras. Generally these images are corrupted by a signal and exposure dependent quantum noise. An automatic image processing carrying out within camera usually implies a gamma and color corrections and an interpolation. And at the same time the noise in the image becomes non-quantum and spatially correlated. This results in a drastic decrease of posterior noise reduction. Considerably better quality of output images can be provided if non-processed Bayer Pattern CFAs (in RAW format) are extracted from a camera and processed on PC. For this case, more effective noise reduction can be achieved as well as better quality image reconstruction algorithms can accessed. The only drawback of storing images in a camera in RAW format is their rather large size. Existing lossless image compression methods provide image compression ratios (CRs) for such images of only about 1.5...2 times. At the same time, a posterior filtering in addition to noise reduction results in appearing losses in the image. Therefore, the use of lossy image compression methods is defensible in this case while final decreasing of effectiveness of noise reduction is inessential. The paper describes a method of adaptive selection of quantization step for each block of a Bayer Pattern CFAs for DCT based image compression. This method allows restricting the decreasing of the posterior noise reduction by only 0.25...0.3 dB. Achieved CRs for the proposed scheme are by 2.5...5 times higher than for strictly lossless image compression methods.
机译：拜耳图案彩色滤光片阵列（CFA）广泛用于数码照片和摄像机。通常，这些图像会因信号和曝光相关的量子噪声而损坏。在相机内执行的自动图像处理通常包含伽马，色彩校正和插值。同时，图像中的噪声变得非量子化并且在空间上相关。这导致后部噪声减少的急剧减少。如果从相机中提取未经处理的Bayer Pattern CFA（RAW格式）并在PC上进行处理，则可以提供质量更高的输出图像。对于这种情况，可以实现更有效的降噪，并且可以访问质量更好的图像重建算法。将图像以RAW格式存储在相机中的唯一缺点是图像尺寸较大。现有的无损图像压缩方法仅能为此类图像提供约1.5 ... 2倍的图像压缩率（CR）。同时，除降噪外，后滤波还会导致图像中出现损失。因此，在这种情况下，有损图像压缩方法的使用是合理的，而降噪效果的最终降低是不必要的。该论文描述了一种针对基于DCT的图像压缩的Bayer Pattern CFA的每个块的自适应选择量化步骤的方法。该方法仅允许将后噪声降低的减小限制为0.25 ... 0.3 dB。与严格的无损图像压缩方法相比，所提出方案的CR值高2.5 ... 5倍。

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