A novel stereo matching technique for radiometric changes using Normalized Cross Correlation

In real world situations, image color values between two stereo images are often affected by various radiometric factors such as illumination direction, illuminant color, and imaging device changes. So, the assumption of color consistency does not hold well in stereo images. Thus, the performance of most conventional stereo matching algorithms would be severely degraded under radiometric variations. The main focus of this work is on illumination invariant stereo matching by generating illumination invariant images from stereo image data using a non-iterative normalisation in log RGB space. The actual stereo matching is done using a local similarity measure, Normalized Cross-Correlation (NCC) which is the standard statistical method for determining similarity which itself is invariant to linear brightness and contrast variations. Error analysis is done by dividing disparity into uniform and discontinuity regions. Experimental results show that our algorithm outperforms other stereo matching algorithms under severely different radiometric conditions between stereo images.