Topic
Dark-frame subtraction
About: Dark-frame subtraction is a research topic. Over the lifetime, 1216 publications have been published within this topic receiving 20763 citations.
Papers published on a yearly basis
Papers
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16 Dec 2011
TL;DR: A method of classification and estimation for impulse noise to reduce the damage to the image detail and blur and shows that the proposed algorithm can reduce the erroneous judgment and enhance the performance of image restoration.
Abstract: To process an image is to treat the images properly, such as in the applications of image noise reduction. The goal of noise reduction is to reduce the damage to the image detail and blur. Many researches are to determine the content of images from pixels. Some researches focus on reducing the noise by the image classification and estimation. The thresholds of these classification algorithms are always depending on their experimental results, or on the fixed form of filtering method. This paper presents a method of classification and estimation for impulse noise to reduce the damage to the image detail and blur. Firstly, we get the standard deviation as the threshold for each pixel in the image. After that, we compare the center pixel to the neighbor pixels of four directions with vertical and horizontal extent. If the difference is greater than the threshold, we judge the center pixel as a noise. The experimental results show that the proposed algorithm can reduce the erroneous judgment and enhance the performance of image restoration.
2 citations
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17 Jul 2013
TL;DR: In this paper, an image processing apparatus and a method for improving horizontal noise is presented. But the method is limited to a single image and is not suitable for a large number of pixels.
Abstract: Disclosed are an image processing apparatus and a method for improving horizontal noise. The image processing apparatus comprises a noise value calculation unit for calculating an average noise value which is an average pixel value of a plurality of object pixels existing in an object pixel region in an optical black region; and a noise removal unit for outputting a pure pixel value obtained by subtracting the average noise value from the pixel value of an active pixel.
2 citations
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24 May 2015TL;DR: This work fabricated a 256×8×5 prototype sensor using a 0.18μm CIS process which achieves a DR of 52.3dB while providing an SNR improvement of 8.8dB over a single-stage linear scanner.
Abstract: Machine vision applications involving the assistance of robots for scene mapping or object classification encounter issues when faced with smooth transparent surfaces, such as glass. Specular reflection from such surfaces saturate the image sensor pixels, restricting their vision of objects beyond the surface. The problem is aggravated by the movement of the robot, making traditional approaches unfeasible. We propose a solution that uses on-chip polarizers to limit the specular reflection and improve scene visibility while overcoming the limited SNR and motion artifacts by using a time delay integration image sensor. We have fabricated a 256×8×5 prototype sensor using a 0.18μm CIS process which achieves a DR of 52.3dB while providing an SNR improvement of 8.8dB over a single-stage linear scanner.
2 citations
01 Jan 2014
TL;DR: A novel method for noise filtering in images using a fuzzy based statistical method that uses the outlierdetection technique to recognize the noise pixels and replaces fuzzy logic techniquewhich depends on the properties of the selected neighbourhood corresponding to a particular noise pixel.
Abstract: Noice removal from images is an important activity for successful processing of images. The main objective of this research work is to investigate the applicability of soft computing techniques and statistical techniques for noice filtering. This paper presents a novel method for noise filtering in images using a fuzzy based statistical method. This method uses the outlierdetection technique to recognize the noise pixels. The pixel values are replaced with fuzzy logic techniquewhich depends on the properties of the selected neighbourhoodcorresponding to a particular noise pixel. Since, the algorithm only changes the pixels identified as the noise pixels, the image distortion of the proposed method is very low.The proposed method was tested with a sample of 60 images. Experimental results havebeen comparedagainst that of median filtermethodwhich is one of the frequently used image noise filtering methods. The comparisonshows that the proposed method generates images with less distortion compared to the median filter method.
2 citations
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TL;DR: Experimental results show that the fuzzy filtering of remote sensing images based on noise checking can effectively remove "salt and pepper" noises.
Abstract: This paper proposes a method named fuzzy filtering of remote sensing images based on noise checking. First, all pixels of input image are separated into noise and signal pixels according to the noise-checking criterion in this method. Second, the noise pixel will be processed based on some theories of fuzzy maths, and the processing result is given to the corresponding pixel of output image; but the signal pixel will not be processed, and its value will be directly given to the corresponding pixel of output image. Furthermore, during the image processing, the value of noise pixel in input image will be replaced by its processing result; which can improve the filtering effect of image. Experimental results show that the method can effectively remove "salt and pepper" noises.
2 citations