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Title:
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AN ADAPTIVE IMAGE SHARPENING SCHEME |
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Author(s):
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Tzong-Jer Chen |
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ISBN:
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978-989-8533-91-3 |
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Editors:
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Katherine Blashki and Yingcai Xiao |
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Year:
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2019 |
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Edition:
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Single |
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Keywords:
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Image Sharpening, Spatial Statistics, Nimble Filter, PFOM |
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Type:
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Short Paper |
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First Page:
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396 |
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Last Page:
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400 |
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Language:
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English |
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Cover:
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Full Contents:
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click to dowload 
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Paper Abstract:
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Image enhancement is one important process for digital images. This processing gives a better subjective visual
appearance. The contours and texture are key features that contain important information essential to the visual quality
aspect. Adaptive image enhancement schemes are proven better than global methods. An adaptive image sharpening
method based on spatial statistics is proposed in this report to effectively sharpen image structures. A noisy Lena was
pre-filtered using a low-pass filter to produce a blurred Lena. The residual image was obtained using average filtering and
then subtracted from the original image. The high-pass residual image should be a combination of structure and noise.
The autocorrelation of each pixel is calculated on the residual image and the image then is sharpened using a nimble filter
based on the adaptive autocorrelation values. The PFOM results show that the similarity of adaptive sharpening is better
than the global scheme. The proposed method will be further developed and applied to improve image acuity, de-noising
and image quality improvement. |
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