Young-yoon Lee

Power-Constrained Contrast Enhancement for Emissive Displays Based on Histogram Equalization

A power-constrained contrast-enhancement algorithm for emissive displays based on histogram equalization (HE) is proposed in this paper. We first propose a log-based histogram modification scheme to reduce overstretching artifacts of the conventional HE technique. Then, we develop a power-consumption model for emissive displays and formulate an objective function that consists of the histogram-equalizing term and the power term. By minimizing the objective function based on the convex optimization theory, the proposed algorithm achieves contrast enhancement and power saving simultaneously. Moreover, we extend the proposed algorithm to enhance video sequences, as well as still images. Simulation results demonstrate that the proposed algorithm can reduce power consumption significantly while improving image contrast and perceptual quality.

Video frame-matching algorithm using dynamic programming

We propose a frame-matching algorithm for video sequences, when a video sequence is modified from its original through frame removal, insertion, shuffling, and data compression. The proposed matching algorithm defines an effective matching cost function and minimizes cost using dynamic programming. Experimental results show that the proposed algorithm provides a significantly lower probability of matching errors than the conventional algorithm.

3D DFT-based video watermarking using perceptual models

In this paper, we propose a multi-bit watermarking technique for video sequences. An N-bit message is embedded in one unit of video fragment, in which a scene is employed as a watermarking unit. The proposed algorithm is fundamentally based on the three-dimensional discrete Fourier transform (DFT). In order to generate a watermark with optimum weighting factors, the perceptual properties for all the three-dimensional DFT coefficients should be computed, but this strategy seems to be undesirable due to the high computational complexity. So, we design a perceptual model of an image in the DFT domain, and apply it to the video watermarking. The proposed perceptual model is expected to give high fidelity and effective, compared to fully calculated visual masks, since it derives all the masks from one reference mask with a well-known estimation method. Through the computer simulations, it can be shown that the proposed watermarking algorithm with the perceptual model yields effective performance for fidelity. Moreover, it was also shown that the proposed scheme provides robustness against various attacks, such as compression, geometric attacks, and collusion attacks.

Multi-bit Video Watermarking Based on 3D DFT Using Perceptual Models

In this paper, we propose a multi-bit watermarking technique for video sequences. An N-bit message is embedded in one unit of video fragment, in which a scene is employed as a watermarking unit. The proposed algorithm is fundamentally based on the three-dimensional discrete Fourier transform (DFT). In order to generate a watermark and optimum weighting factors, the perceptual properties for all the three-dimensional DFT coefficients should be computed. This strategy may require not only high computing complexity but also be undesirable. So, we design a perceptual model of an image in the DFT domain, and apply it to the video watermarking. The proposed perceptual model is expected to give high fidelity, and also its simplified version for video watermarking, estimating visual masks from a reference mask, is effective compared to fully calculated visual masks. Through the computer simulations, it will be shown that the proposed watermarking algorithm with the perceptual model yields effective performance for fidelity. Moreover, it will be also shown that the proposed scheme provides robustness against various attacks, such as compression, geometric attacks, and collusion attacks.

Multi-scale synthetic filtering method for ultrasonic image enhancement

In this paper, a novel ultrasonic image enhancement method, i.e., multi-scale synthetic filtering (MSF) method is proposed for effectively suppressing speckle noise and enhancing structured region. The proposed MSF method is composed of the modified nonlinear coherence diffusion (NCD) model and the adaptive directional filter (ADF) both applied in multi-scale domain. Due to the difference in frequency characteristics of speckle and edge, Laplacian pyramid is adopted to analyze ultrasonic images. On each Laplacian sub-band, the modified NCD is performed to suppress speckle noise while preserving anatomical edges. Then, the ADF is applied to each synthesized images to sharpen and enhance detailed boundaries. The performance of the proposed MSF method is compared with the speckle reducing anisotropic diffusion (SRAD). For quantitative analysis, the contrast-to-noise ratio (CNR) values were computed on in vivo carotid artery ultrasound images. When compared with the SRAD, the average CNR gain of the proposed MSF method was 0.42 dB. The average processing time of the proposed method is 8.1 ms per one frame. The clinical evaluations and short running time indicate that the proposed MSF method can improve the diagnostic confidence in medical ultrasound imaging.