A Comparative Study on Adaptive Local Image Registration Methods

Adaptive Local Image Registration based on adaptive filtering can register both grayscale images and color images. Here the local distortions are corrected without explicitly estimating the displacement field. A filter of appropriate size convolves with reference image and gives the pixel values corresponding to the distorted image and the filter is updated in each stage of the convolution. When the filter converges to the system model, it provides the registered image. In this method the 2-D image plane is mapped into a 1-D sequence using space-filling curves. Adaptive Local Image Registration can be implemented in two ways as Pixel-By-Pixel Method and Block-Based Method. This work did a comparative study between these two methods. The two methods are tested using different types of geometrically distorted images and the quantitative performance evaluation is done using Mean Squared Error (MSE), Mean Absolute Error (MAE), Peak Signal-to-Noise Ratio (PSNR) and Structural Similarity (SSIM) index. The Block-Based method shows better performance than Pixel-By-Pixel Method.