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.

Transducer noise in a photoreceptor

Abstract: IN our attempts to unravel the workings of visual systems, we seek neural responses and interactions which can account for visual behaviour. A popular measure of visual performance is the threshold intensity at which a stimulus is detected with a given probability. To account for these detection tasks, one must not only measure neural signals at threshold1,2, but also find the limiting sources of variance (that is, the noise) both within3 and outside4,5 the nervous system6. The manner in which the random nature of photon absorptions can limit the performance of visual systems is well understood4,5,7,8. When bleaching effects are negligible, photon absorptions follow the Poisson distribution. Consequently photon counts derived from the same mean signal have a variance equal to their mean. These fluctuations in counts are an inherent property of photon signals and are referred to as photon shot noise. Processes within the visual system generate intrinsic noise7, but to assess its effect on thresholds one must first account for photon shot noise. This is generally difficult because photon catch cannot be measured directly, and must be estimated from optical parameters which are subject to significant error7. We have estimated the levels of photon shot noise and intrinsic transducer noise9 in locust photoreceptors at low light intensities. We have chosen to search for sources of intrinsic noise in the visual system of the locust because it has recently been shown that, at low intensities, each effective photon produces a single, large quantum bump10 (Fig. 1). Thus, we measure precisely the number of photons contributing to photoreceptor signals and derive, from the total response variance, that additional variance due to intrinsic noise. We report here that the transducer noise mimics the properties of photon shot noise, is of similar magnitude, and, in most conditions, must have an equally significant role in determining thresholds.

Noise reduction of image sequences using adaptive motion compensated frame averaging

Abstract: A scheme for noise reduction of image sequences by adaptively switching, on a block-by-block basis, between simple (nondisplaced) frame averaging and motion-compensated frame averaging is represented. The resulting noise reduction approaches that achievable with simple frame averaging, while maintaining the good image resolution achievable for motion compensated frame averaging. >

Adaptive error diffusion with improved edge and sharpness perception

Abstract: A method for adaptive error diffusion. The method includes the steps of receiving input image data, detecting edges in the input image data, and then adding noise to the input image data depending upon results of said edge detection. The amount of noise is higher for pixels with higher edge content, unless the pixel is on an edge that is already sharp. Once the noise is added the method performs error diffusion on the noise-enhanced image data and it produces output image data. Alternatively, noise can be added to the thresholding portion of the error diffusion process.

Reduction of Speckle Noise and Image Enhancement of Images Using Filtering Technique

Abstract: Reducing noise from the medical images, a satellite image etc. is a challenge for the researchers in digital image processing. Several approaches are there for noise reduction. Generally speckle noise is commonly found in synthetic aperture radar images, satellite images and medical images. This paper proposes filtering techniques for the removal of speckle noise from the digital images. Quantitative measures are done by using signal to noise ration and noise level is measured by the standard deviation.