Department of Electrical and Electronics Engineering
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Item DWT based image super resolution performance analysis(IJRET, 2016-12) Bhatt, Upendra MohanIn computer vision field, Image resolution enhancement has become the most current research area. Improving image resolution by applying costly hardware is expensive and time-consuming. Many algorithms have been developed by researchers based on Projection Onto Convex Set (POCS), Maximum-aposteriori (MAP) and Maximum Likelihood (ML) In this paper, we analyzed a super resolution algorithm based on Discrete Wavelet Transform (DWT). Single frame super resolution can be achieved by use of different interpolation method but this scheme generates blur at the edges of images. Hence in this paper we relied on wavelet transform for super resolution algorithm with different orthogonal and bi-orthogonal filters. Quality aspect of images such as MSE, PSNR, SSIM and Correlation Coefficient (CC) are calculated with this proposed algorithm.Item A Review on Image Resolution Enhancement Methods in Spatial and Frequency Domain(IJCSMC, 2016-06) Bhatt, Upendra MohanZooming a picture is ver essential in the field where someone wants to obtain more detailed information from an image. Low resolution(LR) images do not contain more information so to retrieve more information from that image Super-resolution(SR) is applied on LR images. The resolution enhancement work began in 1984 when Tsai and Huang [1] has introduced a mathematical model to obtain a single high-resolution image from a single or multiple LR images. This paper provides the review of the work done in the area of super-resolution in the spatial as well as in the frequency domain. This paper is organized into following sections. Section II describes spatial domain methods of super-resolution, section III gives method in the frequency domain, section IV contains comparison between some of the well-known algorithms and finally in the last section Conclusion is drawn.Item Image super resolution based on discrete and Stationary wavelet transform using Canny edge extraction and non local mean(IEEE, 2017-01) Bhatt, Upendra MohanThis paper addresses the issue of generating a high-resolution(HR) image from single low quality or low-resolution(LR) image. In this work, Discrete wavelet transform (DWT) is used with the Stationary wavelet transform (SWT) to generate or increase the resolution of the image. SWT reduces the translation invariance presence in DWT. To preserve the edges Canny edge extraction is used to get the sharper image. To interpolate the image into the intermediary stage of proposed algorithm Lanczos interpolation is used and to reduce the artifacts introduced by the DWT Non-local mean(NLM) filter has been used. The experimental result shows that the proposed algorithm gives good results based on image quality parameters as compared with the state-of-the-art works in super resolution (SR) process.Item Comparision between sizes of original HR images and images obtained through super resolution(IEEE, 2018-02) Bhatt, Upendra MohanGetting high detailed information through LR(low resolution) images is not possible, so research in the field of computer science leads toward converting the LR images to the HR(high resolution) images and this process is known as Super resolution. In this paper a super resolution algorithm is proposed which uses DWT and SWT to downsampled the images and to preserve the edges Canny edge extractor and to remove the noise NLM filter is added to the algorithm. This paper shows the comparision between the sizes of original HR images on which experiment is done and the images obtained after converting LR image to HR with this algorithm. Result shows that the HR image obtained after the experiment is so much lesser in size than original HR image