Abstract
According to recent advances in digital image processing techniques, interest in high-quality images has been increased. This paper presents a resolution enhancement (RE) algorithm based on the pyramid structure, in which Laplacian histogram matching is utilized for high-frequency image prediction. The conventional RE algorithms yield blurring near-edge boundaries, degrading image details. In order to overcome this drawback, we estimate an HF image that is needed for RE by utilizing the characteristics of the Laplacian images, in which the normalized histogram of the Laplacian image is fitted to the Laplacian probability density function (pdf), and the parameter of the Laplacian pdf is estimated based on the Laplacian image pyramid. Also, we employ a control function to remove overshoot artifacts in reconstructed images. Experiments with several test images show the effectiveness of the proposed algorithm.
Highlights
In most electronic imaging applications, resolution enhancement (RE) of images containing high-density pixels with high detail is desired and often required [1]
The Laplacian pyramid represents a set of bandpass/highpass images, from which we can estimate the HF image needed for RE by utilizing statistical characteristics of the Laplacian pyramid images, in which the normalized histogram of the Laplacian image data is fitted to the Laplacian pdf and the parameter of the Laplacian pdf is estimated based on the Laplacian pyramid images
The predicted HF image using the global constant β and the control function C(x, y) considering the local activity is added to the interpolated input image, in which three parameters (β, M0, and c0) are used
Summary
In most electronic imaging applications, resolution enhancement (RE) of images containing high-density pixels with high detail is desired and often required [1]. One application is to reconstruct a higher-quality digital image from a low-resolution (LR) image that is obtained with an inexpensive camera/camcorder for printing or frame-freeze purpose. Another application is conversion from a National Television System Committee (NTSC) video signal to a high-definition television (HDTV) signal to display a standard video signal on HDTV with less visual artifacts. RE of digital images corresponds to reduction of the spatial sampling interval, in which HF components of the resolution-enhanced images become larger. For effective RE of digital images, it is necessary to estimate by some means the HF components that are lost in image data acquisition
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