Image noise level detection and removal system and method
First Claim
1. An image processing system comprising:
- a noise detection circuit comprising,an observed image local statistical extraction circuit that extracts a first local statistical characteristics from an observed image,a low-pass filter design circuit that designs a low-pass Gaussian filter according to the first local statistical characteristics from the observed image,a predicted noise image generation circuit that generates a predicted noise image using the low-pass Gaussian filter,a predicted noise image local statistical extraction circuit that extracts a second local statistical characteristics from the predicted noise image,a predicted original image local statistical extraction circuit that extracts a third local statistical characteristics from a predicted original image using the first local statistical characteristics of the observed image and the second local statistical characteristics of the predicted noise image, anda noise classification circuit that sets a flag level indicating a noise level for each pixel of the observed image according to the third local statistical characteristics of the predicted original image; and
a noise removal circuit that sets a filter size according to the flag level and that removes noise, when the flag level for the each pixel of the observed image is determined at the noise classification circuit.
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Abstract
An image processing system and method is provided. The image processing system includes extracting a first local statistical characteristics from an observed image, generating a low-pass filter according to the first local statistical characteristics to generate a predicted noise image, and extracting second local statistical characteristics from the predicted noise image, extracting a third local statistical characteristics from a predicted original image using the first local statistical characteristics of the observed image and the second local statistical characteristics of the predicted noise image, and setting a flag level indicating a noise level for each pixel of the observed image according to the third local statistical characteristics of the predicted original image to detect noise, and setting a filter coefficient according to the flag level of the detected noise to remove the noise, and restoring the observed image.
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Citations
11 Claims
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1. An image processing system comprising:
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a noise detection circuit comprising, an observed image local statistical extraction circuit that extracts a first local statistical characteristics from an observed image, a low-pass filter design circuit that designs a low-pass Gaussian filter according to the first local statistical characteristics from the observed image, a predicted noise image generation circuit that generates a predicted noise image using the low-pass Gaussian filter, a predicted noise image local statistical extraction circuit that extracts a second local statistical characteristics from the predicted noise image, a predicted original image local statistical extraction circuit that extracts a third local statistical characteristics from a predicted original image using the first local statistical characteristics of the observed image and the second local statistical characteristics of the predicted noise image, and a noise classification circuit that sets a flag level indicating a noise level for each pixel of the observed image according to the third local statistical characteristics of the predicted original image; and a noise removal circuit that sets a filter size according to the flag level and that removes noise, when the flag level for the each pixel of the observed image is determined at the noise classification circuit. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9)
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10. An image processing method comprising:
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extracting a first local statistical characteristics from an observed image; generating a low-pass filter according to the first local statistical characteristics to generate a predicted noise image; extracting a second local statistical characteristics from the predicted noise image; extracting a third local statistical characteristics from a predicted original image using the first local statistical characteristics of the observed image and the second local statistical characteristics of the predicted noise image; setting a flag level indicating a noise level for each pixel of the observed image according to the third local statistical characteristics of the predicted original image so as to detect noise; setting a filter coefficient according to the flag level of the detected noise to remove the noise; and restoring the observed image. - View Dependent Claims (11)
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Specification