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  • 學位論文

基於人眼視覺配合YCbCr色彩模型特性與亮度變化之飽和度調整模型

Saturation Adjustment Model Based on Human Vision with YCbCr Color Model Characteristics and Luminance Changes

指導教授 : 江正雄

摘要


隨著科技日益的進步,影像已經邁向數位化與高品質的年代。為因應未來人們對於高品質與鮮豔色彩的需求,色彩調整的方式將會愈來愈被重視。調整色彩主要的因素為: 1.消費者的需求;2.人眼視覺特性;3.色彩模型特性。因為其調整後的色彩是由人眼所觀看,所以色 彩調整不僅要符合理論也要符合人眼所觀察的結果。傳統的色彩調整 方式大部份只是調整或增強色彩的對比度與飽和度以達到更鮮豔的色彩與更清晰的影像,但是在過程中往往會發生過飽和的情況。其過飽和會使得飽和度增加,同時也使影像觀看起來不太自然。再加上為了顯示色彩須要對過飽和做再修正的動作,會使得色彩的資訊量流失,使得預期達到的結果將會產生變化。所以本論文提出了一飽和度調整模型來解決此問題。 本文提出一飽和度調整模型基於人眼視覺配合YCbCr色彩模型特性與亮度變化。過去大多數人在做色彩調整時,大都是以分別將亮度與飽和度調整到最好為主要方法,但是經常會發生過飽和的情形發生,使得影像變得較不自然。本文利用曝光補償來模擬當明亮度變化時亮度、飽和度與色相三者之間的關係。根據模擬發現飽和度會隨著亮度變化所改變,也發現其色彩移動模式與YCbCr模型有相呼應的關係。最後,再加上人眼視覺特性來做修正,以達到更好的效果。根據實驗結果可以發現影像色彩的明亮度、對比度與鮮豔度都有所提升,且不會有過飽和的情況發生,影像也較為自然。

並列摘要


This thesis proposes a saturation adjustment method based on human vision with YCbCr color model characteristics and luminance changes. In the traditional color adjustment approach, people tried to separately adjust the luminance and saturation. However, this approach makes the color over-saturate very easily and makes the image look unnatural. In this work we try to use the concept of exposure compensation to simulate the brightness changes and to find the relationship among luminance, saturation, and hue. The simulation indicates that saturation changes with the change of luminance and the simulation also shows there are certain relationships between color variation model and YCbCr color model. Together with all these symptoms, we also include the human vision characteristics to propose a new saturation method to enhance the vision effect of an image. The experimental results show that the proposed approach can make the image have better vivid and contrast. Most important of all, unlike the over-saturation caused by the conventional approach, our approach prevents over-saturation and further makes the adjusted image look natural.

參考文獻


[1] Capra, A., Castrorina, A., Corchs, S., Gasparini, F., Schettini, R., "Dynamic range optimization by local contrast correction and histogram image analysis," International Conference on Consumer Electronics, pp.309-310, 7-11 Jan. 2006
[2] Yadong Wu, Zhiqin Liu, Yongguo Han, Hongying Zhang, "An image illumination correction algorithm based on tone mapping," International Congress on Image and Signal Processing, vol.2, pp.645-648, 16-18 Oct. 2010
[3] Sungmok Lee, Homin Kwon, Hagyong Han, Gidong Lee, Bongsoon Kang, "A Space-Variant Luminance Map based Color Image Enhancement," IEEE Transactions on Consumer Electronic, vol.56, no.4, pp.2636-2643, November 2010
[4] Xinghao Ding, Xinxin Wang, Quan Xiao, "Color image enhancement with a human visual system based adaptive filter," International Conference on Image Analysis and Signal Processing, pp.79-82, 9-11 April 2010
[5] Yihua Shi, Jinfeng Yang, Renbiao Wu, "Reducing Illumination Based on Nonlinear Gamma Correction," IEEE International Conference on Image Processing, vol.1, pp.I-529-I-532, Sept. 16 2007-Oct. 19 2007

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