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Papers by Amisha Shah

Research paper thumbnail of Single Image Super-Resolution via Non Sub-sample Contourlet Transform based Learning and a Gabor Prior

International Journal of Computer Applications, 2013

Enhancing the quality of image is a continuous process in image processing related research activ... more Enhancing the quality of image is a continuous process in image processing related research activities. For some applications it becomes essential to have best quality of image such as in forensic department, where in order to retrieve maximum possible information, image has to be enlarged in terms of size, with higher resolution and other features associated with it. Such obtained high quality images have also a concern in satellite imaging, medical science, High Definition Television (HDTV), etc. In this paper a novel approach of getting high resolution image from a single low resolution image is discussed. The Non Sub-sampled Contourlet Transform (NSCT) based learning is used to learn the NSCT coefficients at the finer scale of the unknown high-resolution image from a dataset of high resolution images. The cost function consisting of a data fitting term and a Gabor prior term is optimized using an Iterative Back Projection (IBP). By making use of directional decomposition property of the NSCT and the Gabor filter bank with various orientations, the proposed method is capable to reconstruct an image with less edge artifacts. The validity of the proposed approach is proven through simulation on several images. RMS measures, PSNR measures and illustrations show the success of the proposed method.

Research paper thumbnail of A Technique to Preserve Edge Information in Single Image Super Resolution

Procedia Computer Science, 2016

Goal of image super resolution is to enhance the size of an image without upsetting the inherited... more Goal of image super resolution is to enhance the size of an image without upsetting the inherited information. The quality of an enhanced image is conserved if the information around all kind of edges is preserved. The proposed novel approach potted the information around curvature edges and hard edges (abrupt transition in intensity) using Non Sub-Sampled Contourlet Transform (NSCT) based learning process. Furthermore the smoothness of smooth edges (gradual transition in intensity) is preserved by using soft edge smoothness prior as a regularizing parameter. The validity of the proposed approach is proven through simulation on several images.

Research paper thumbnail of A Novel Approaoch based on Optical Flor for Moving Object Detection

Software Engineering and Data Engineering, 2010

Research paper thumbnail of Image Super Resolution-A Survey

Improving image quality has always been an issue of image technology. Enhancing the quality of im... more Improving image quality has always been an issue of
image technology. Enhancing the quality of image is a continuous
ongoing process. For some applications it becomes essential to
have best quality of image such as in forensic department, where
in order to retrieve maximum possible information image has to
be enlarged in terms of size. For example sometimes in forensic
investigations either criminal face or in video surveillance a
licences number plate, increased image size helps to extract
minute information embedded in the image. During this exercise
beyond a certain limit, the enlarged image results in a blurred
picture. Most possible cause of this problem is the hardware
limitation, primarily which includes the sampling rate of a
Charge- Coupled Device [CCD]. Especially this becomes very
critical while capturing a high speed moving object. In such case
pre/post-image processing is required which in turn restores the
High resolution (HR) / Super resolution (SR) image(s) from the
captured low resolution (LR) image(s). Such obtained high quality
images have also a concern in satellite imaging, medical science,
high Definition Television (HD TV), etc. There are various
techniques to attain an image with higher resolution. In this paper
some of the approaches of super resolution are discussed.

Research paper thumbnail of Single Image Super-Resolution via Non Sub-sample Contourlet Transform based Learning and a Gabor Prior

International Journal of Computer Applications, 2013

Enhancing the quality of image is a continuous process in image processing related research activ... more Enhancing the quality of image is a continuous process in image processing related research activities. For some applications it becomes essential to have best quality of image such as in forensic department, where in order to retrieve maximum possible information, image has to be enlarged in terms of size, with higher resolution and other features associated with it. Such obtained high quality images have also a concern in satellite imaging, medical science, High Definition Television (HDTV), etc. In this paper a novel approach of getting high resolution image from a single low resolution image is discussed. The Non Sub-sampled Contourlet Transform (NSCT) based learning is used to learn the NSCT coefficients at the finer scale of the unknown high-resolution image from a dataset of high resolution images. The cost function consisting of a data fitting term and a Gabor prior term is optimized using an Iterative Back Projection (IBP). By making use of directional decomposition property of the NSCT and the Gabor filter bank with various orientations, the proposed method is capable to reconstruct an image with less edge artifacts. The validity of the proposed approach is proven through simulation on several images. RMS measures, PSNR measures and illustrations show the success of the proposed method.

Research paper thumbnail of A Technique to Preserve Edge Information in Single Image Super Resolution

Procedia Computer Science, 2016

Goal of image super resolution is to enhance the size of an image without upsetting the inherited... more Goal of image super resolution is to enhance the size of an image without upsetting the inherited information. The quality of an enhanced image is conserved if the information around all kind of edges is preserved. The proposed novel approach potted the information around curvature edges and hard edges (abrupt transition in intensity) using Non Sub-Sampled Contourlet Transform (NSCT) based learning process. Furthermore the smoothness of smooth edges (gradual transition in intensity) is preserved by using soft edge smoothness prior as a regularizing parameter. The validity of the proposed approach is proven through simulation on several images.

Research paper thumbnail of A Novel Approaoch based on Optical Flor for Moving Object Detection

Software Engineering and Data Engineering, 2010

Research paper thumbnail of Image Super Resolution-A Survey

Improving image quality has always been an issue of image technology. Enhancing the quality of im... more Improving image quality has always been an issue of
image technology. Enhancing the quality of image is a continuous
ongoing process. For some applications it becomes essential to
have best quality of image such as in forensic department, where
in order to retrieve maximum possible information image has to
be enlarged in terms of size. For example sometimes in forensic
investigations either criminal face or in video surveillance a
licences number plate, increased image size helps to extract
minute information embedded in the image. During this exercise
beyond a certain limit, the enlarged image results in a blurred
picture. Most possible cause of this problem is the hardware
limitation, primarily which includes the sampling rate of a
Charge- Coupled Device [CCD]. Especially this becomes very
critical while capturing a high speed moving object. In such case
pre/post-image processing is required which in turn restores the
High resolution (HR) / Super resolution (SR) image(s) from the
captured low resolution (LR) image(s). Such obtained high quality
images have also a concern in satellite imaging, medical science,
high Definition Television (HD TV), etc. There are various
techniques to attain an image with higher resolution. In this paper
some of the approaches of super resolution are discussed.

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