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25 April 2007 Local statistics based filtering method for enhancement in super-resolution image reconstruction
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Abstract
A local statistics based contrast enhancement technique for enhancing the reconstructed high resolution image from a set of shifted and rotated low resolution images is proposed in this paper. Planar shifts and rotations in the low resolution images are determined by a phase correlation approach performed on the polar coordinate representations of their Fourier transforms. The pixels of the low resolution images are expressed in the coordinate frame of the reference image and the image values are interpolated on a regular high-resolution grid. The non-uniform interpolation technique which allows for the reconstruction of functions from samples taken at non-uniformly distributed locations has relatively low computational complexity. Since bi-cubic interpolation produces blurred edges due to its averaging effect, the edges of the reconstructed image are enhanced using a local statistics based approach. The center-surround ratio is adjusted using global statistics of the reconstructed image and used as an adaptive gamma correction to achieve the local contrast enhancement which increases the image sharpness. Performance of the proposed algorithm is evaluated by conducting experiments on both synthetic and real image sets and the results are encouraging in terms of visual quality.
© (2007) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Numan Unaldi and Vijayan K. Asari "Local statistics based filtering method for enhancement in super-resolution image reconstruction", Proc. SPIE 6575, Visual Information Processing XVI, 657508 (25 April 2007); https://doi.org/10.1117/12.722134
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