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.

Bit-depth extension of digital displays by quantizing noise-compensated image data

Abstract: A method for extending bit-depth of display systems. The method includes the steps of measuring the static display noise of a display device (14), using the display noise to create pseudo-random noise (12) and subtracting the pseudo-random noise (12) from a contone image (10). After the noise-compensated image data is quantized and displayed, the noise in the display device (14) will substantially convert the noise-compensated image data back to contone image data with few or no contouring artifacts. Other embodiments include using the inherent noise of the human visual system (22) instead of the static display noise, or both. Specific adjustments can be made to the noise of the human visual system (22) for color displays.

Digital camera identification based on canonical correlation analysis

Abstract: In this paper, we introduce a new method for digital camera identification from its color images using image sensor noise. We first compute the two noise reference patterns by averaging the noise component from two groups of color images taken with a camera. Then we use canonical correlation analysis (CCA) to calculate the projection directions of the two noise reference patterns. Finally, we calculate the correlation coefficient between the projection of the noise from a specific color image onto one projection direction and the projection of one of noise reference patterns onto another projection direction, then use this coefficient to decide whether the specific color image was taken by the camera or not. Experimental results show that the presented method provides higher accuracy than other methods on the condition of using a few images to compute reference pattern.

Method for the non-medical X-ray image processing and arrangement for carrying out the method

Abstract: The invention relates to a method for the non-medical X-ray image processing for determining the spatial distribution of the noise and of the sensitivity in an X-ray image. The noise or sensitivity image, respectively, can be generated by pixel-by-pixel subtraction of two X-ray pictures whilst a noise image can also be generated by forming the square root in each individual pixel of an X-ray picture.

New Approach For Noise Removal From Digital Image

Abstract: Most of the nonlinear filters used in removal of noise work in two successive phases, i.e. noise detection followed by filtering, only the corrupted pixels keeping uncorrupted ones intact. Performance of such filters is dependent on the performance of detection schemes. In this work, thrust has been put to devise an accurate detection scheme and a improved adaptive filtering mechanism. The proposed method consists of noise detection followed by the removal of detected noise by median filter using selective pixels that are not noise themselves. The noise detection is based on simple thresholding of pixels. Computer simulations were carried out to analyse the performance of the proposed method and the results obtained were compared to that of conventional median filter and center weighted median (CWM) filter and mean filter.

Research of properties of digital noise in contrast images

Abstract: The article is devoted to the research of probabilistic properties of digital noise in contrast images. For obtaining numerical characteristics of the additive noise distribution physical experiments were made. These characteristics testify that noise in digital images is non-uniform both on variance and on distribution are received were for this purpose made. The image with contrast overfall from black to white was simulated and the noise filtration is carried out by known methods of smoothing. During a Monte-Carlo method of statistical tests it was established that smoothing based on the generalized method of the least absolute values eliminates noise on contrast overfall more efficiently.