Dr. Tatsumi Watanabe Profile

Dr. Tatsumi Watanabe

at Panasonic Communications Co Ltd

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Proceedings Article | 13 January 2003 Paper

Improvement of color quality with modified linear multiscale retinex

Tatsumi Watanabe, Yasuhiro Kuwahara, Akio Kojima, Toshiharu Kurosawa

Proceedings Volume 5008, (2003) https://doi.org/10.1117/12.472030

KEYWORDS: Reflectivity, Image quality, Image processing, Visualization, RGB color model, Image compression, Visibility, Digital cameras, Cameras, Charge-coupled devices

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With popular of Digital Still Camera-DSC, higher image quality is required. One of the subjects is that image quality at shadow area caused by the narrow dynamic range of the CCD devices is improved automatically. Conventionally, gamma transformation, histogram equalization, and etc. have been utilized for this improvement, but these are not always enough improvement. Recently, examinations applying to retinex theory taking into account of human eyes characteristics proposed by Land are paid attention. This algorithm renders image at shadow area clearly and effectively using spatial information between surrounding pixels arranged into two dimensions. Typical methods are Single-scale retinex(SSR) and Multi-Scale Retinex(MSR). These methods, however, does not always work on practical use in terms of color correction of the printed images with different RGB density distribution. In order to improve the issues of MSR, we propose the Modified Linear Multi-scale retinex (ML-MSR) method. A modified method consists of (a) linear computation processing and (b) synthesis both the original images and the images obtained by the linear MSR. By the simulation for the images printed by DSC, we show that ML-MSR can improve the visibility at shadow areas keeping with both the color balance and saturation, comparing with the conventional methods, such as histogram equalization and MSR proposed by Jobson. In general, a processing time of MSR remarkably increases with the size of Gaussian averaging filter to compute the weighted average. We describe about faster processing method of the ML-MSR algorithm, which has been shorten by using the thinning out of surrounding pixels and simplicity of average processing.

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