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Improved NAS RIF blind image recovery method

An image and degraded image technology, applied in image enhancement, image data processing, instruments, etc., can solve the problems of noise sensitivity and high-frequency noise amplification

Inactive Publication Date: 2007-01-24
BEIHANG UNIV
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  • Abstract
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  • Claims
  • Application Information

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Problems solved by technology

However, since the inverse filtering process is a high-pass filter, which brings about the problem of high-frequency noise amplification, the method is very sensitive to noise. In addition, the correctness of the support domain has a great impact on the restoration results of the method. In the original NAS- The definition of the support domain in the RIF method is the smallest rectangle containing the target object

Method used

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  • Improved NAS RIF blind image recovery method

Examples

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Effect test

Embodiment 1

[0094] Embodiment 1: as Figure 6 shown. (a) is the source image with 256 pixels*128 pixels and the background gray level is 0; (b) is the blurred image with Gaussian white noise with mean value 0 and variance 10; (c) is the original NAS-RIF method restoration The results of ; (d) The restoration results of the improved NAS-RIF method. Experiments show that the improved method has a good restoration effect, and when the number of iterations is less than 10, its cost function has tended to be stable, and it takes about 39s. When using the original method, the cost function is basically stable when the number of iterations is less than 40, and the time-consuming is about 153s.

Embodiment 2

[0095] Embodiment 2: as Figure 7 As shown, (a) is the original image, its background gray value is 0, and its size is 128 pixels*128 pixels; (b) Gaussian white noise with a mean value of 0 and a variance of 5 is added to the blurred image; (c) is the original The restoration results of the NAS-RIF method; (d) is the restoration effect of the improved method. The cost function of the original method needs to iterate about 40 times to converge, and the time spent is about 139s, while the improved method only needs to iterate about 10 times, and the time spent is about 46s, which greatly shortens the time of image processing.

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Abstract

The present invention belongs to the field of image treating technology, and is especially improved image restoration method. The improved image restoration method includes the following steps: 1. Lee filtering the degenerate image to eliminate noise influence; 2. determining the image supporting area by means of threshold partitioning process; 3. inverse filtering to obtain estimated image; 4. projecting the estimated image to one real image space with one NL filter; 5. low pass filtering the NL filter output image; 6. finding out the difference values; 7. correcting the coefficients with the difference values; and 8. repeated correcting until the difference values are converged to minimum values to complete the image restoration. The present invention has raised support threshold precision, powerful anti jamming capacity and shortened running time.

Description

technical field [0001] The invention belongs to the image processing technology and relates to the improvement of the existing image restoration method. Background technique [0002] Image restoration is the process of estimating real images from observed degraded images. Its imaging model can be expressed as [0003] g(x,y)=f(x,y)*h(x,y)+n(x,y)[1] [0004] where g(x, y) is the observed degraded image, and f(x, y) is the target original image. The physical meaning of h(x, y) is instantaneous impulse function or point spread function. In order to estimate the original image from the degraded image with little (or almost no) relevant point spread function and prior knowledge of the original image, Kundur et al. proposed a recursive inverse filter based on a limited support domain (ie NAS-RIF) blind image restoration method, this method does not need to know the system point spread function h(x, y), and only uses the support domain range of the original image as ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T5/00
Inventor 江洁张广军吕博李苏祺
Owner BEIHANG UNIV
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