Department of Electrical and Electronics Engineering

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Subject: search.filters.subject.Canny edge extraction

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    Performance analysis of wavelet filter bank for an image super resolution algorithm
    (IEEE, 2017-07) Bhatt, Upendra Mohan
    Image super-resolution is a technique in which a high-resolution image is generated using a single or multiple low-resolution images. In this paper, an image super-resolution algorithm is proposed in which Discrete wavelet transform (DWT) is used to generate different frequency sub-bands of the image and Stationary wavelet transform (SWT) overcomes the issue of lack of translation invariance of DWT so it is used here with DWT. To preserve more edge information Canny Edge extraction operator has been applied to the input image and subbands are interpolated using Lanczos interpolation. The high-frequency sub bands and the input image are passed through Non-Local Mean (NLM) filter to reduce the artifacts generated by DWT. Different orthogonal and bi-orthogonal filters have been applied to this algorithm and different quality parameters such as PSNR, MSE, RMSE, SSIM and Correlation coefficient are calculated. It is found that db2 wavelet is showing better results.
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    Image super resolution based on discrete and Stationary wavelet transform using Canny edge extraction and non local mean
    (IEEE, 2017-01) Bhatt, Upendra Mohan
    This 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.
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    Comparision between sizes of original HR images and images obtained through super resolution
    (IEEE, 2018-02) Bhatt, Upendra Mohan
    Getting 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