Edge parameter computing method for image and image noise omitting method utilizing the edge parameter computing method
AssigneeSilicon Motion, Inc.
InventorChun-Wen Chang
Life of this patent
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Abstract
An edge parameter computing method for an image, wherein the image includes a plurality of pixels forming a Bayer pattern. The edge parameter computing method comprises: (a) computing an average grey level of at least one specific type pixels in a specific region of the image; (b) computing each grey level difference value between the average grey level and the specific type pixels in the specific region to generate a plurality of grey level difference values; (c) finding a specific pixel with a maximum grey level difference value according to the grey level difference values; and (d) computing a ratio value between the average grey level and the maximum grey level difference value as the edge parameter.
Claims18
A method for computing an edge parameter of an image, wherein the image includes a plurality of pixels forming a Bayer pattern, wherein the method comprises:
- (a) computing an average grey level of at least one specific type pixels in a specific region of the image;
- (b) computing each grey level difference value between the average grey level and the specific type pixels in the specific region to generate a plurality of grey level difference values;
- (c) finding a specific pixel with a maximum grey level difference value according to the grey level difference values;
- and
- (d) computing a ratio value between the average grey level and the maximum grey level difference value as the edge parameter.
A noise omitting method for an image, wherein the image includes a plurality of pixels forming a Bayer pattern, where the method comprises:
- (a) computing an average grey level of at least one specific type pixels in a first region of the image;
- (b) computing each grey level difference between the average grey level and the specific type pixels to generate a plurality of grey level difference values;
- (c) finding a specific pixel with a maximum grey level difference value according to the grey level difference values;
- (d) determining a second region according to the specific pixel and a target pixel in the first region;
- and
- (e) selectively utilizing the pixel in the second region to adjust a grey level value of the target pixel to omit noise.
Dependencies are inferred from the claim text.