Donggyun Kim

Adaptive defogging with color correction in the HSV color space for consumer video surveillance systems

Consumer video surveillance systems often suffer from bad weather conditions, observed objects lose visibility and contrast due to the presence of atmospheric haze, fog, and smoke. In this paper, we present an image defogging algorithm with color correction in the HSV color space for video processing. We first generate a modified transmission map of the image segmentation using multiphase level set formulation from the intensity (V) values. We also estimate atmospheric light in the intensity (V) values. The proposed method can significantly enhance the visibility of foggy video frames using the estimated atmospheric light and the modified transmission map. Another contribution of the proposed work is the compensation of color distortion between consecutive frames using the temporal difference ratio of HSV color channels. Experimental results show that the proposed method can be applied to consumer video surveillance systems for removing atmospheric artifacts without color distortion.

Fully digital auto-focusing system with automatic focusing region selection and point spread function estimation

We present a fully digital auto-focusing (FDAF) system with automatic focusing region selection and a priori estimated dataset of circularly symmetric point-spread functions (PSFs). The proposed approach provides realistic, unsupervised PSF estimation by analyzing the entropy and edge information in the automatically selected focusing region. The main advantage of the proposed system is the fast and robust estimation of a defocusing PSF due to simply selecting the optimal PSF in small, homogeneous region-ofinterest. The proposed FDAF system consists of functional units; i) focusing region selection, ii) PSF selection by generating the major step response in the region from the blurred input image, and iii) image restoration using the selected PSF. Experimental results show the proposed focusing region selection method is more effective than the traditional methods, and the resulting image of the FDAF system provides high visual quality with appropriately amplified details in the image. For this reason, the proposed algorithm can realize low-cost, intelligent focusing function for various image acquisition devices, such as digital cameras, mobile phone cameras, and consumers camcorders.

Lens distortion correction and enhancement based on local self-similarity for high-quality consumer imaging systems

In this paper, a novel image enhancement system for a wide-angle lens camera is presented. The proposed system consists of; i) lens distortion correction using space-varying interpolation kernels and ii) image restoration based on the local self-similarity. The correction process for the geometric distortion produced by a wide-angle lens results in radial distortion artifacts caused by non-linear resampling. To reduce such artifacts, the proposed algorithm uses space-varying interpolation kernels derived from the lens calibration data. The corrected image is further enhanced using self-example-based image restoration. Experimental results demonstrate the proposed method can correctly remove the geometric distortion and further enhance the quality of the radially interpolated image.

Extended fisheye lens model for practical geometric correction and image enhancement

An extended fisheye lens model is presented to control the size ratio between the distorted and virtually undistorted images based on orthographic projection. The optimum size ratio is derived to correct the barrel distortion of a fisheye lens so that the maximum amount of the peripheral region is reconstructed with the minimum visual distortion. The geometric correction generates an aliasing artifact in the central region and a jagging artifact in the peripheral region. Based on the proposed lens model, a novel image enhancement algorithm is also presented to remove the aliasing and jagging artifacts in the geometrically corrected image. Experimental results demonstrate that the proposed enhancement method outperforms existing methods in the sense of objective and subjective measures.

Flicker-free low-light video enhancement using patch-similarity and adaptive accumulation

Recently, the various low-light enhancement methods have been proposed for consumer electronic devices. Although the existing methods provide the better brightness enhancement results, these methods generate the flicker effects during the video enhancement process. Flicker effects are caused by ignoring the correlation information between adjacent frames (i.e. inter-frames). To minimize the flicker effects, the proposed method uses the patch-similarity and adaptive accumulation in the inter-frames domain, and it makes the mean brightness values of enhanced video frames be preserved. The experimental results show that the proposed method can better improve the video frames without flicker effects than existing enhancement methods, and it can be applied to the image signal processing (ISP) chain for consumer electronic devices.

Non-dyadic lens distortion correction and enhancement of fish-eye lens images

In this paper, a novel image enhancement method is presented for a fish-eye lens camera. In order to remove jagging and blur artifacts that are generated by a correction process of geometric lens distortion, the proposed method searches similar patches in a non-dyadic scale space. For further enhancing the artifact-removed image, a self-example-based image restoration is also used. Experimental results show that the proposed method can successfully remove not only geometric distortion of a fish-eye lens but also jagging and blur artifacts in the corrected image.

High-resolution digital zooming using a fisheye lens and geometric compensation

A computational camera uses unconventional optics and digital signal processing software to produce new forms of visual information [1]. This paper presents a computational ca mera approach to near-lossless, high-quality digital zooming using a fisheye lens. Conventional digital zooming systems employed in compact consumers imaging devices result in severe distortions in output images due to the limited amount of information. In spite of such lim ited quality, the digital z ooming function is e quipped in many inexpensive cameras because of its desirable properties, such as compactness, low power consumption, and low cost. In order to overcome the limited quality of the conventional digital zooming system, we use a fisheye lens with appropriate digital image processing algorithms. For realization of the proposed computational camera-based digital zooming, we fir stge nerate input test images using a commercial optical simulator. We then calibrate the fisheye lens using a special rectangular grid patterns. Finally, we remove the barrel distortion in the output of the fisheye lens, and crop an appropriate size of rectangular region in the center. Experimental results indicate that the proposed computational camera-based digital zooming system can significantly increase the resolution of output images compared with conventional digital zooming systems, especially at magnification ratio of 3 or higher.

Continuous digital zooming of asymmetric dual camera images using registration and variational image restoration

This paper presents a theoretical basis to realize a high-quality digital zooming using two camera modules with different focal lengths. First, we describe an image degradation model of the asymmetric dual camera system to analyze the characteristic of the wide- and tele-view images. In an asymmetric dual camera system, we assume that the shorter focal length module produces the wide-view image with the low-resolution. On the other hand, the longer focal length module produces the tele-view image by an optical zooming. To reconstruct a wide-view image of a continuous digital zooming, the proposed method first estimates the point spread function (PSF) between the wide- and tele-view images. Next, the proposed method performs variational-based image restoration using the estimated PSF. In addition, since the tele-view image inserted into appropriate region of the wide-view image, the proposed method can provide significantly improved wide-view image.

Inter-Conversion Matrix for Transcoding Block DCT and DWT-Based Compressed Images

This study derived the inter-conversion matrices, which can be used in heterogeneous image transcoding between the compressed images using different transforms, such as the 8×8 block discrete cosine transform (BDCT) and the one-level discrete wavelet transform (DWT). Basically, to obtain the one-level DWT coefficients from 8×8 BDCT, inverse BDCT should be performed followed by forward DWT, and vice versa. On the other hand, if the proposed interconversion approach is used, only one inter-conversion matrix multiplication makes the corresponding transcoding possible. Both theoretical and experimental analyses showed that the amount of computation of the proposed approach decreases over 20% when the inter-conversion matrices are used under specific conditions.

Selective frequency decomposition in the wavelet domain for single image-based super-resolution

This paper presents single-image based super-resolution (SR) algorithm using selective frequency decomposition in the wavelet domain. We synthesize the diagonal high-frequency (HH) sub-band of the discrete wavelet transform (DWT) using the low frequency component of the low-resolution (LR) image and the high frequency component of the bi-cubic interpolated image in the HH sub-band of the DWT. The reconstructed HR image is obtained by inverse wavelet transforming the synthesized HH sub-band together with the remaining three sub-bands. The HR image is further enhanced using directional edge sharpening. The proposed single-image based SR algorithm can be used to provide digital zoom or SR functions for consumer imaging devices such as mobile phone cameras, camcorders, and surveillance cameras. Experimental results demonstrate that the proposed algorithm outperforms the existing single-image based SR algorithms in the sense of having reconstructed high-frequency components with minimum ringing artifacts.