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.

Digital picture noise reduction by combining high-noise and low-noise processed pictures

Abstract: A method for processing a digital picture is disclosed. The method may include steps (A) to (C). Step (A) may generate a first picture by processing the digital picture using a first noise reduction technique in a circuit. Step (B) may generate a second picture by processing the digital picture using a second noise reduction technique. The first noise reduction technique may achieve a higher noise reduction than the second noise reduction technique. Step (C) may generate an output picture by combining the first picture and the second picture.

Performance of Haze Removal Filter for Hazy and Noisy Images

Abstract: s- Haze and noise performance detection (HNPD) filter is proposed for impulse noise and haze removal in images. In this approach, the noisy pixels are detected in single phase, based on a set of irreplaceable connection criteria. Simulation results show that the HNPD filter outperforms others at medium to high noise rates and suppresses impulse noise and haze effectively while preserving image details, even thin edges. Keywords—Haze, Noisy image, Single phase, Haze removal filter. I. In tr o du c ti o n Dig ital images are often affected by impulse and salt pepper noise during their acquisition or transmission processes (1). Median filtering is an efficient nonlinear technique widely used for impulse and salt pepper noise removal. However, it tends to remove desirable details and produces haziness and spots in restored images. To remove impulse noise as well as to preserve fine details, various filters are proposed with noise detector schemes, such as the tri-state median (TSM ) filter (1). Haze and noise are different to remove fro m images and have different techniques to solve these problems. We want to give a co mmon technique to remove haze and noise. They show good performance at low noise rates, but still fail to suppress impulse noise effectively and preserve image details, particularly at noise rates greater than 30%. In this Letter, we propose a single phase noise detection technique to detect a random valued impulse noise, which is distributed uniformly in the dynamic range of (0, 255) (2-3). At first median filtering (4) is applied. In this paper proposed approach is based on sufficient akin neighbour criteria, a pixel that has at least a certain number of similar pixels among its neighbours in the filtering window is considered to be an original p ixel. A significant feature of the offered method is that its performance remains relatively constant over a wide range of noise rates and it is able to effectively suppress impulse noise (5) in heavily corrupted images . HNPD is a comb ination of these two median filtering and guided filtering. The remaining part of this paper as follows II section covers the haze and noise removal, III section covers the performance parameters, IV part includes the simulation results and final V section covers the conclusion remark and future work.

Signal processor, signal processing method and digital camera

Abstract: PROBLEM TO BE SOLVED: To provide a signal processor, a signal processing method and a digital camera capable of reducing noise while preventing the partial deterioration of image quality. SOLUTION: A microcomputer 40 detects a pixel located at an edge of an image displayed by an image signal outputted form a CCD 24 and controls a noise reduction processing part 29 so as not to perform noise reduction processing of pixels located at the edge and so as to perform noise reduction processing of the other pixels. COPYRIGHT: (C)2006,JPO&NCIPI

Image pickup apparatus capable of reducing noise in image signal and method for reducing noise in image signal

Abstract: Noise included in image data output from an analog processing unit, is eliminated by a noise reduction circuit. The noise reduction circuit restricts a difference between a value of each of peripheral pixels and a value of a center pixel to a value a value having a predetermined noise constant defined as an upper limit with respect to each of the peripheral pixels, e.g., a pixel space of 5×5. The values of the peripheral pixels whose upper limits are restricted are defined as new values of the peripheral pixels. The value of the center pixel is converted into a value obtained by averaging the new values of the peripheral pixels and the value of the center pixel. In this manner, low pass filter processing is carried out.

Noise reduction for machine vision systems

Abstract: A method for reducing noise in an image from an image capture device includes filter the image using both an offset fixed pattern noise filter and a gain fixed pattern noise filter. Thereafter, the image is filtered using a remnant fixed pattern noise filter to reduce remnant fixed pattern noise.