Abstract:
This paper proposes an algorithm that enhances the contrast of an input image using interpixel contextual information. The algorithm uses a 2-D histogram of the input ima...Show MoreMetadata
Abstract:
This paper proposes an algorithm that enhances the contrast of an input image using interpixel contextual information. The algorithm uses a 2-D histogram of the input image constructed using a mutual relationship between each pixel and its neighboring pixels. A smooth 2-D target histogram is obtained by minimizing the sum of Frobenius norms of the differences from the input histogram and the uniformly distributed histogram. The enhancement is achieved by mapping the diagonal elements of the input histogram to the diagonal elements of the target histogram. Experimental results show that the algorithm produces better or comparable enhanced images than four state-of-the-art algorithms.
Published in: IEEE Transactions on Image Processing ( Volume: 20, Issue: 12, December 2011)
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- IEEE Keywords
- Index Terms
- Contrast Agent ,
- Contextual Information ,
- Input Image ,
- Image Contrast ,
- Diagonal Elements ,
- Neighboring Pixels ,
- Image Histogram ,
- Computational Complexity ,
- Grayscale ,
- Dynamic Range ,
- Minimum Distance ,
- Minimal Differences ,
- Image Regions ,
- Color Images ,
- Face Recognition ,
- Output Image ,
- Subband ,
- Image Enhancement ,
- Neighborhood Level ,
- Bright Regions ,
- Database Of Subjects ,
- Mean Brightness ,
- Enhancement Algorithm ,
- Histogram Equalization ,
- Histogram Matching ,
- Enhancement Values ,
- Tridiagonal Matrix ,
- High Contrast ,
- Average Brightness ,
- Color Space
- Author Keywords
Keywords assist with retrieval of results and provide a means to discovering other relevant content. Learn more.
- IEEE Keywords
- Index Terms
- Contrast Agent ,
- Contextual Information ,
- Input Image ,
- Image Contrast ,
- Diagonal Elements ,
- Neighboring Pixels ,
- Image Histogram ,
- Computational Complexity ,
- Grayscale ,
- Dynamic Range ,
- Minimum Distance ,
- Minimal Differences ,
- Image Regions ,
- Color Images ,
- Face Recognition ,
- Output Image ,
- Subband ,
- Image Enhancement ,
- Neighborhood Level ,
- Bright Regions ,
- Database Of Subjects ,
- Mean Brightness ,
- Enhancement Algorithm ,
- Histogram Equalization ,
- Histogram Matching ,
- Enhancement Values ,
- Tridiagonal Matrix ,
- High Contrast ,
- Average Brightness ,
- Color Space
- Author Keywords