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.

Methods for suppressing structured noise in a digital image

Abstract: A method for suppressing structured noise in a digital image includes creating a smoothed version of the original image. Monotonic and slowly-varying image regions are detected by analyzing a residual image which is the function of the original image and its smoothed version. A local window is defined in each pixel location identified in the thresholding process as the location with structured noise and samples inside the window are randomly permuted to randomize the noise structures. A noise-filtered version of the original residual image is generated. The noise-filtered residual and the smoothed version of the original image are combined to produce a final image.

A new salt and pepper noise removal filtering algorithm

Abstract: A new filtering algorithm on eliminating salt and pepper noise is presented. The pixel value of the algorithm lies on the average pixel values of its neighbourhood. If the noise density is small, we may estimate and remove the most serious contaminated pixels in the template, and then find the average of remaining pixels within the template. This average is the value of the pixel denoising. In the case of large noise density, the average of point has been obtained by the top three pixels and one pixel on the left is the request. Experiment results show that the new algorithm is good in performance to keep the content of image and remove noise, especially in the case of strong noise and small window.

A cluster merging filter for noise smoothing

Abstract: Due to the statistical nature of X-rays and the electromagnetic field, medical images produced by these energy sources are contaminated with random noise, which degrades the image quality. Because of this effect, considerable effort has been devoted to removing noise from medical images. The authors present a new method of image noise smoothing. This method uses the natural separation of distinct populations in each window to evaluate a given pixel. In this way, more pixels that belong to the population are included in the cluster of the given pixel, and fewer pixels that do not belong to the population are erroneously included. The image smoothing is further enhanced by the join-count statistic. By implementing join-count statistics, clusters that were erroneously separated by a large variation of random noise were evaluated and merged. This operation provides better results, enhancing noise smoothing, especially in the areas with largely uniform pixels. As a result, the smoothing performance is enhanced while the preservation of edges is maintained. >

Digital subtraction angiograph

Abstract: PROBLEM TO BE SOLVED: To reduce quantum noises of X-rays and improve the guiding property of a catheter by suppressing the specific picture element value of a subtraction image and the positive or negative display gradation. SOLUTION: An X-ray high-voltage device 1 applies a high voltage to an X-ray tube display via the control signal from a CPU circuit 13 and irradiates X-rays to a subject 3. An optical image is formed by an image intensifier 4, it is photographed by a TV camera 5, and it is stored in a frame memory 11 as it is without being processed by an arithmetic unit 8. Gradation conversion and rewriting of the content of a lookup table 12 are made by the instruction of the CPU 13. The quantum noise of X-rays is normally distributed centering on 0 by subtraction, and the output is suppressed to 0 against the input in the fixed width centering on 0 to reduce the quantum noise. When the width for suppressing the output to 0 is changed and adjusted while the image is observed by the instruction of the CPU 13, the noise can be reduced.

Quantification of color motion picture quality considering human visual sensitivity

Abstract: When a color video system with highly accurate color reproduction is designed, a good measure is required for evaluating the image quality including the color reproduction There are some degradation sources in a total imaging system from image acquisition to image reproduction Color random noise is one of major degradations which is often added in image capture phase In this paper, we investigate the performance of the S-CIELAB (spatial CIELAB) and STCIELAB (spatiotemporal CIELAB) color difference as a quality measure in color motion picture degraded by random noise In the experiment, we added a spatiotemporal noise to three kinds of still images and two kinds of motion pictures, performed the observer evaluation experiment, and found the noise level at which the noise is just noticeable Color differences between images which correspond to just noticeable noise level by human observers were measured by CIELAB, S-CIELAB and ST-CIELAB space In this paper, we report the performance of S-CIELAB and ST-CIELAB compared to CIELAB