色彩恆定演算法之硬體研究

Abstract

人眼在不同的光源下可以感知物體為相同的顏色，這種能力稱為色彩恆常 性。而在數位相機中，物體的顏色是由sensor 記錄物體反射進來的光線，這個顏色 會跟隨光源的不同而變化。導致實際相片的顏色和人眼感覺到的不同。這個問題 己經有提出很多的演算法來解決，這些方法也被稱為自動白平衡。近年來數位相 機和手機相機非常的普遍，使得把這些演算法應用到即時系統是很重要的課題。 本篇論文首先會廣泛的介紹主要的色彩恆定的演算法，並且測量這些演算法 的效能，而這些演算法也會實現成硬體，並套用在本篇論文所提出的系統架構中， 以方便用來比較各種不同演算法所需耗費的成本。根據比較的結果，我們利用現 有的灰世界演算法和色域演算法，提出一個結合兩者優點的新演算法；當色域演 算法辨識的結果數目夠少時使用色域演算法，反之則使用灰世界演算法。經大量 不同光源的影像實驗後，顯示出本演算法在效能上超越其他種類的演算法，而且 硬體成本也在可接受的範圍內。

Abstract Humans are able to recognize the color of objects independently of the light sources, which is called as color constancy. In a digital still camera, a sensor is used to measure the reflected light, and the measured color at each pixel varies according to the color of the illuminant. Therefore, the resulting colors may not be the same as those perceived by users. Many algorithms have been developed to solve the color constancy problem, which is sometimes also called as auto white balance. Since digital cameras and mobile phones equipped with cameras became more and more popular in recently years, the selection of color constancy algorithms for realtime system implementation is an important issue. In this thesis, we first provide a comprehensive introduction to the field of color constancy, where the major color constancy algorithms are described. The performance of these algorithms are then evaluated, and the hardware cost of some algorithms are analyzed with a proposed system framework. Furthermore, based on the analysis results, we also propose a new algorithm by taking advantages of existing Gamut Mapping and modified Gary World algorithms. Gamut Mapping algorithm is employed when the number of recognized illuminants is small enough, and modified Gray World algorithm is employed for other cases. After comparing with other color constancy methods with a large date sets of images recording objects under different light sources, the experiments show that the proposed color constancy algorithm achieves the best performance with acceptable hardware cost.