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The main objective of this paper is to present a reliable approach to compute an approximate solution of Jeffery-Hamel flow by using the modified homotopy perturbation method coupled with sumudu transform. The method finds the solution without any discretization or restrictive assumptions and avoids the round-off errors. The fact that this technique solves nonlinear problems without using Adomian's polynomials can be considered as a clear advantage of this algorithm over the decomposition method. The numerical solutions obtained by the proposed method indicate that the approach is easy to implement and computationally very attractive.

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The main objective of the super resolution images is to enhance the quality of the multiple lower resolution images. Super Resolution image is constructed by using raw images. An Image with improved resolution is always desirable for various applications like satellite, medical etc. to enhance the qualitative features are the images. In this paper, Super Resolution Image Reconstruction (SRIR) is proposed for improving the resolution of lower resolution images. Proposed approach is described as follows. Initially, Some low resolution images of same scene which are usually translated, rotated and blurred are used to form a super resolution image. Then, the image registration operation translated, orients, scaled and rotated images in the similar way to that of source image. Next, Lifting Wavelet Transform (LWT) with Daubechies4 coefficients are applied to color components of each image due to its less memory allocation compared to other wavelet techniques. Further, Set Portioning in Hierarchical Trees (SPIHT) technique is appliedfor image compression as it possess lossless compression, fast encoding/decoding, and adaptive nature. The three low resolution images are fused by spatial image fusion method. The noise is removed by dual tree Discrete Wavelet Transform (DWT) and blurring is reduced by blind deconvolution. Finally, the samples are interpolated to original samples to obtain a super resolution image. The structural similarity for each intermediate image is compared to the source image to observe high structural similarity by objective analysis. Gabor transform is also implemented for image enhancement and edge detection.