Satellite Image Contrast Enhancement Using Discrete Wavelet Transform and Singular Value Decomposition Hasan Demirel‚ Cagri Ozcinar‚ and Gholamreza Anbarjafari Abstract—In this letter‚ a new satellite image contrast enhancement technique based on the discrete wavelet transform (DWT) and singular value decomposition has been proposed. The technique decomposes the input image into the four frequency subbands by using DWT and estimates the singular value matrix of the low–low subband image‚ and‚
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Abstract This paper is about a selected few image processing applications. Optical Character Recognition is the translation of images of handwritten‚ typewritten or printed text into machine-editable text. Then I have introduced the captcha that we so frequently encounter in common websites. An algorithm trying to solve or break a captcha has been explained. Face detection is a growing and an important tool in security these days. It must be applied before face recognition. There are many
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Elementary Introduction to Image Processing Based Robots 2009 Acknowledgement P age |2 • My Senior Sourabh Sankule • My Friends Mayank and Ashish • Robotics Club‚ IIT Kanpur • Electronics Club‚ IIT Kanpur • Centre for Mechatronics‚ IIT Kanpur Ankur Agrawal IIT Kanpur P age |3 Contents Introduction ................................................................................................................ 4 MATLAB ............................................
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from the Greek phōtos means "light" and graphos means "drawing"‚ together meaning "drawing with light". Photography is the art‚ science‚ and practice of creating durable images by recording light or other electromagnetic radiation‚ either chemically by means of a light-sensitive material or electronically by means of an image sensor. Photography has many uses for business‚ science‚ manufacturing‚ art‚ recreational purposes‚ and mass communication. Modern photography has raised a number of concerns
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video sequences. The fourth video sequence reached 97.6% and the third 90.6%. In TEST 2‚ the iris detection was above 96% in all five video sequences with two above 99.7% and two at 100%. Face size estimation is also above 99.9%. The average processing time of our method was 0.02 s per frame. Thus‚ the proposed method can process frames at a rate near to 50 frames/s‚ and therefore‚ is applicable in real time in a standard personal computer (PC 1.8 GHz). Index Terms—Anthropometric templates
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NOISE REDUCTION BY USING FUZZY IMAGE FILTERING ABSTRACT The existing system available for fuzzy filters for noise reduction deals with fat-tailed noise like impulse noise and median filter. Only impulse noise reduction uses fuzzy filters. Gaussian noise is not specially concentrated; it does not distinguish local variation due to noise and due to image structure. The proposed system presents a new technique for filtering narrow-tailed and medium narrow-tailed noise by a fuzzy filter. The system
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DIGITAL IMAGE PROCESSING (CREATIVE WORLD OF FACE MORPHING) BY ABSTRACT A study on face morphing is proposed.The algorithms explains the extra feature of points on face and based on these feature points‚ images are portioned and morphing is performed. The algorithms has been used to generate morphing between images of face of different people as well as between images of face of individuals. To do face morphing‚ feature points are usually specified manually
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high-resolution (HR) image from single or multiple low-resolution (LR) images‚ known as “super-resolution” has been a problem. High resolution means high pixel density‚ also referred to as high-definition (HD). An HR image brings out details that would be blocked out in an LR image. More pixels in the same area imply a higher sampling frequency thereby offering more details. Due to the tremendous progress in sensor and chip manufacturing techniques‚ we can now obtain high resolution images from a high-end
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Koeller 1 ESL 118 Prof. Shields April 7‚ 2014 Final Draft An image that speaks Some photos never leave one’s memory. The photo that I choose for this essay is one such photo. It is the Pulitzer prize-winning photograph taken in 1994 in Sudan by Kevin Carter during the Sudan famine depicting a child about to
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Lecture 13: Edge Detection c Bryan S. Morse‚ Brigham Young University‚ 1998–2000 Last modified on February 12‚ 2000 at 10:00 AM Contents 13.1 Introduction . . . . . . . . . . . . . . 13.2 First-Derivative Methods . . . . . . . 13.2.1 Roberts Kernels . . . . . . . . . 13.2.2 Kirsch Compass Kernels . . . . 13.2.3 Prewitt Kernels . . . . . . . . . 13.2.4 Sobel Kernels . . . . . . . . . . 13.2.5 Edge Extraction . . . . . . . . . 13.3 Second-Derivative Methods . . . . . . 13.3.1 Laplacian Operators
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