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RAW Image Reconstruction Using a Self-contained sRGB–JPEG Image with Small Memory Overhead
International Journal of Computer Vision ( IF 11.6 ) Pub Date : 2017-12-18 , DOI: 10.1007/s11263-017-1056-0
Rang M. H. Nguyen , Michael S. Brown

Most camera images are saved as 8-bit standard RGB (sRGB) compressed JPEGs. Even when JPEG compression is set to its highest quality, the encoded sRGB image has been significantly processed in terms of color and tone manipulation. This makes sRGB–JPEG images undesirable for many computer vision tasks that assume a direct relationship between pixel values and incoming light. For such applications, the RAW image format is preferred, as RAW represents a minimally processed, sensor-specific RGB image that is linear with respect to scene radiance. The drawback with RAW images, however, is that they require large amounts of storage and are not well-supported by many imaging applications. To address this issue, we present a method to encode the necessary data within an sRGB–JPEG image to reconstruct a high-quality RAW image. Our approach requires no calibration of the camera’s colorimetric properties and can reconstruct the original RAW to within 0.5% error with a small memory overhead for the additional data (e.g., 128 KB). More importantly, our output is a fully self-contained 100% compliant sRGB–JPEG file that can be used as-is, not affecting any existing image workflow—the RAW image data can be extracted when needed, or ignored otherwise. We detail our approach and show its effectiveness against competing strategies.

中文翻译:

使用具有小内存开销的独立 sRGB-JPEG 图像重建 RAW 图像

大多数相机图像保存为 8 位标准 RGB (sRGB) 压缩 JPEG。即使将 JPEG 压缩设置为最高质量,编码的 sRGB 图像在颜色和色调处理方面也得到了显着处理。这使得 sRGB-JPEG 图像对于许多假设像素值和入射光之间存在直接关系的计算机视觉任务来说是不可取的。对于此类应用程序,首选 RAW 图像格式,因为 RAW 表示经过最少处理的、特定于传感器的 RGB 图像,该图像与场景辐射呈线性关系。然而,RAW 图像的缺点是它们需要大量的存储空间,并且没有得到许多成像应用程序的良好支持。为了解决这个问题,我们提出了一种方法来对 sRGB-JPEG 图像中的必要数据进行编码,以重建高质量的 RAW 图像。我们的方法不需要对相机的色度属性进行校准,并且可以将原始 RAW 重建到 0.5% 的误差范围内,而附加数据的内存开销很小(例如,128 KB)。更重要的是,我们的输出是一个完全独立的 100% 兼容 sRGB-JPEG 文件,可以按原样使用,不会影响任何现有的图像工作流程——RAW 图像数据可以在需要时提取,否则可以忽略。我们详细介绍了我们的方法,并展示了其对抗竞争策略的有效性。不影响任何现有的图像工作流程——RAW 图像数据可以在需要时提取,否则可以忽略。我们详细介绍了我们的方法,并展示了其对抗竞争策略的有效性。不影响任何现有的图像工作流程——RAW 图像数据可以在需要时提取,否则可以忽略。我们详细介绍了我们的方法,并展示了其对抗竞争策略的有效性。
更新日期:2017-12-18
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