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.

Method of reducing noise in image and image processing apparatus using the same

Abstract: Provided are methods and apparatuses for reducing noise in an image, in which a kernel that gives a weight to a pixel value with respect to determination of a similarity between patches is adaptively changed according to a reference patch, a non-transitory computer-readable storage medium for recording the same, and an image processing apparatus using the same, in which noise in an image is removed according to a noise removal algorithm based on non-local means.

PARIGI: a Patch-based Approach to Remove Impulse-Gaussian Noise from Images

Abstract: In this paper, we present an implementation of the PARIGI method that addresses the problem of the restoration of images affected by impulse noise or by a mixture of Gaussian and impulse noise. The method relies on a patch-based approach, which requires careful choices for both the distance between patches and for the statistical estimator of the original patch. Experiments are performed in the case of pure impulse noise and in the case of a mixture of Gaussian and impulse noise.

Correction of background noise in direct digital dental radiography.

Abstract: OBJECTIVES To clarify the source of noise in direct digital intra-oral radiography with RVG-S (Trophy Radiologie, Vincennes, France) and to use these to develop a method for correction of background noise. METHODS Sensor temperature, image acquisition time and X-ray dose were independently analysed with the IPLab Spectrum (Signal Analytics, Vienna, VA) software. RESULTS The decrease in pixel value due to the dark current was linearly related to the image acquisition time. Although a variation in sensitivity was observed when the sensor was exposed to X-rays, the mean pixel value of the entire image was linearly related to the exposure time. The image showing only the signal due to X-ray dose was derived from the original RVG-S image by correcting for the dark current and the pixel-by-pixel sensitivity variation of the CCD sensor. CONCLUSION The image formed only by X-ray dose distribution can be derived by correcting for the background noise.

Noise reduction methods for hybrid subtraction

Abstract: In digital subtraction angiography, hybrid subtraction provides selective vessel images free of soft-tissue motion artifacts but with a lower signal-to-noise ratio (SNR) than temporal subtraction images. An image processing method called measurement-dependent filtering has been developed to enhance the SNR of hybrid images without losing resolution or selectivity. Linear combinations of four images consisting of a pre- and postcontrast dual-energy measurement pair form both the hybrid image and a lower noise but less selective vessel image. The noise-reduced image is derived by combining the low-frequency components of the hybrid image with the high-frequency components of the lower noise image in a variety of ways. The results of the filtering method, when tested on both phantom and clinical data, display images with about the same degree of conspicuity as the hybrid image and a SNR approaching that of the temporal image.

Contrast focus figure-of-merit method that is insensitive to scene illumination level

Abstract: A method, system and program product for providing automatic focus adjustment for an image device, comprising the steps of: differentiating an image along some axis to obtain a difference image; computing a variance of the difference image; determining a noise contribution to the variance; subtracting the noise contribution from the variance; using the adjusted noise variance as a factor in making the automatic focus adjustment. In a preferred embodiment, the variance is normalized, and the noise contribution is determined by determining the shot noise and the read noise.