We propose an unsharp-masking technique which preserves the hue of colors in images. This method magnifies the contrast of colors and spatially sharpens textures in images. The contrast magnification ratio is adaptively controlled. We show by experiments that this method enhances the color tone of photographs while keeping their perceptual scene depth.

We present a simple technique for enhancing multi-modal images. The unsharp masking (UM) is at first nonlinearized to prevent halos around large edges. This edge-preserving UM is then extended to cross-sharpening of multi-modal images where a component image is sharpened with the aid of more clear edges in another component image.

We proposed a method for reducing LCD motion blur in MPEG domain and analyzing the cause of LCD motion blur. The problem of LCD motion blur is caused by slow response time of liquid crystal and hold-type displaying method of LCDs. The proposed method uses MPEG motion vectors and frequency coefficients of DCT blocks to improve the motion blurs. First, we interpreted the aperture and response time effect of LCD in frequency domain then, modeled sharpening mask filters for the compensation. We confirmed the reduction of motion blurs in LCDs by a motion image simulator.

In this paper, we show that motion sharpening phenomenon can be explained as a form of visual masking for a special case where a video sequence is composed of alternate frames with different level of sharpness. A frame of higher sharpness behaves to mask the ambiguity of a subsequent frame of lower sharpness and hence preserves the perceptive quality of the whole sequence. Borrowing the mechanism for visual masking, we formulated a quantitative model for deriving the minimum spatial frequency conditions which preserves the subjective quality of the frames being masked. The quantitative model takes into account three fundamental properties of the video signals, namely the size of motion, average luminance and the power of each frequency components. The psychophysical responses towards the changes of these properties are obtained through subjective assessment tests using video sequences of simple geometrical patterns. Subjective experiments on natural video sequences show that more than 75% of viewers could make no distinction between the original sequence and the one processed using the quantitative model.

This paper presents a new multistage comb-rotated sinc (RS) decimator with a sharpened magnitude response. Novelty of this paper is that the multistage structure has more design parameters that provides additional flexibility to the design procedure. It uses different sharpening polynomials and different cascaded comb filters at different stages. As the comb filters at the latter stages are of lower order than that of the original comb filter, the use of more complex sharpening polynomials at latter stages is possible. This leads to an improvement of the frequency characteristic without a significant increase in the complexity of the overall filter. The comb filter of the first stage is realized in a non-recursive form and can be implemented in a computationally efficient form by making use of the polyphase decomposition of the transfer function in which the subfilters operate at a lower rate that depends on the down-sampling factor employed in the first stage. In addition, both multipliers of the rotated sinc (RS) filter of the second stage work at a lower rate.

Digital halftoning is used to quantize a grayscale image to a binary image. Error diffusion halftoning generates a high-quality binary image, but also generates some defects such as the warm effect, sharpening, and so forth. To reduce these defects, Kite proposed a modified threshold modulation method that utilizes a multiplicative parameter for controlling sharpening. Nevertheless, some degradation was observed near the edges of objects with a large luminance change. In this paper, we propose a method of controlling the multiplicative parameter in proportion to the magnitude of the local edge slope. The results of computer simulation show a greater reduction of sharpening in the halftone image. In particular, there is a great improvement in the quality of the edges of objects with a large luminance change.

Computation of scale space images requires numerical integration of partial differential equations, which demands large computational costs especially in nonlinear cases. In this paper, we present a computational scheme for nonlinear scale spaces based on iterated filtering of original images. This scheme is found to be a special case of numerical integration with a particularly adapted integration steplength. We show the stability of the iteration with local windows and that with global ones and analyze the deformation of edge waveforms in the filtering. Computational costs are evaluated experimentally for both local and global windows and finally we apply the nonlinear multi-scale smoothing to contrast enhancement of images.

An image edge sharpening technique with phase correction for digital image is presented. In this paper the point spread functions of a typical standard single focal lens and zoom lens are investigated with a several different apertures. And from this investigation the Fourier phase figure pattern of the point-spread function is identified. The technique here includes a traditional one (a Laplacian operator) and phase-only synthesis with the corrected Fourier phase. The Fourier phase of the original non-blurred image is estimated recursively and it is utilized for implementation of the phase-only synthesis, which is powerful for image edge sharpening. A human visual property is also introduced as a weight function in order to maintain the natural smoothness in the gray level of the resulting processed image. Simulation examples show that the proposed technique is superior to the traditional one.

This paper proposes a new method for automatic improvement in image quality through adjusting the image sharpness. This method does not need prior knowledge about image blur. To improve image quality, the sharpness must be adjusted to an optimal value. This paper shows a new method to evaluate sharpness without MTF. It is considered that the human visual system judges image sharpness mainly based upon edge area features. Therefore, attention is paid to the high spatial frequency components in the edge area. The value is defined by the average intensity of the high spatial fequency components in the edge area. This is called the image edge sharpness" value. Using several images, edge sharpness values are compared with experimental results for subjective sharpness. According to the experiments, the calculated edge sharpness values show a good linear relation with subjective sharpness. Subjective image sharpness does not have a monotonic relation with subjective image quality. If the edge sharpness value is in a particular range, the image quality is judged to be good. According to the subjective experiments, an optimal edge sharpness value for image quality was obtained. This paper also shows an algorithm to alter an image into one which has another edge sharpness value. By altering the image, which achieves optimal edge sharpness using this algorithm, image sharpness can be optimally adjusted automatically. This new image improving method was applied to several images obtained by scanning photographs. The experimental results were quite good.