Gray-preserving color correction without exposure value information

Jianping Zhou

doi:10.1117/12.760807

28 January 2008 Gray-preserving color correction without exposure value information

Jianping Zhou

Proceedings Volume 6807, Color Imaging XIII: Processing, Hardcopy, and Applications; 68070Q (2008) https://doi.org/10.1117/12.760807
Event: Electronic Imaging, 2008, San Jose, California, United States

Abstract

Digital cameras are widely used in many applications, such as digital still cameras, camcorders, camera phones, and video surveillance. Advances in large resolution CCD/CMOS sensors coupled with the availability of low-power image signal processors have led to the development of digital cameras with both high resolution image and short visual clip capabilities. The red, green, or blue color values obtained from a camera sensor are device-dependent. Thus there is a need to characterize these values in a device-independent fashion and provide a color correction. For simplicity, common methods presume a linear transformation to perform the color conversion. The problem translates to finding the transformation matrix and the offset vector. One well known approach uses a white-preserving constraint in the optimization. This approach requires that source data and reference data have the same exposure values. However, source data and reference data usually have different exposure values, and exposure information is either unavailable or inaccurate. We propose a new method that provides color conversion by linear transformation optimization with gray preservation. Our method allows for differing exposures between images from the target sensor and the color reference. Experiments show that images resulted from our method look more colorful than those from previous methods.

Citation Download Citation

Jianping Zhou "Gray-preserving color correction without exposure value information", Proc. SPIE 6807, Color Imaging XIII: Processing, Hardcopy, and Applications, 68070Q (28 January 2008); https://doi.org/10.1117/12.760807

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