Multi Focus Image Fusion Using Discrete Wavelet Transform

Image fusion is the process of combining complementary information from multiple input images of the same scene into an image, so that the resultant image contains a more accurate description of the scene than any of the individual source images. Only the portions of an image would appear sharp which comes on the focus of the camera and thus the concept of multi-focus image fusion comes into picture. The two basic fusion techniques are pixel level and region level fusion. Pixel level fusion deals with the operations on each and every pixel separately. The various techniques implemented under this method are averaging, stationary wavelet transform, discrete wavelet transform (DWT), principal component analysis (PCA). The most appreciated approach in region-based method is using the concept of spatial frequency with block method. The main drawback of this method is it is not an automatic method. In this paper, simple and efficient pixel level technique using wavelet transform is proposed. Experimental results on two pairs of multi-focus images like forensic images are compared in terms of extended spatial frequency and standard deviation as performance parameters. On the basis of these parameters, we can conclude that the proposed pixel level fusion technique is better compared to other pixel level fusion techniques.