Seungwon Jung

The presence of haze in the atmosphere degrades the quality of images captured by visible camera sensors. The removal of haze, called dehazing, is typically performed under the physical degradation model, which necessitates a solution of an ill-posed inverse problem. To relieve the difficulty of the inverse problem, a novel prior called dark channel prior (DCP) was recently proposed and has received a great deal of attention. The DCP is derived from the characteristic of natural outdoor images t

In this letter, we propose an improved histogram modification based reversible data hiding technique. In the proposed algorithm, unlike the conventional reversible techniques, a data embedding level is adaptively adjusted for each pixel with a consideration of the human visual system (HVS) characteristics. To this end, an edge and the just noticeable difference (JND) values are estimated for every pixel, and the estimated values are used to determine the embedding level. This pixel level adjustm

In this paper, we present an adaptive joint trilateral filter (AJTF), which consists of domain, range, and depth filters. The AJTF is used for the joint enhancement of images and depth maps, which is achieved by suppressing the noise and sharpening the edges simultaneously. For improving the sharpness of the image and depth map, the AJTF parameters, the offsets, and the standard deviations of the range and depth filters are determined in such a way that image edges that match well with depth edg

In scalable video coding (SVC) as an extension of H.264/advanced video coding (AVC), a computationally expensive exhaustive mode decision is employed to select the best coding mode for each macroblock (MB). In order to reduce computational complexity, we propose a fast mode decision algorithm for SVC which uses an all-zero block (AZB) detection. Based on the empirical analysis of the inter-layer correlation of the AZB, the MB at the enhancement layer (EL) is predicted whether to be the AZB. Then

In this paper, we present a novel depth sensation enhancement algorithm considering the behavior of human visual system (HVS) toward stereoscopic image displays. On the basis of the recent studies on the just noticeable depth difference (JNDD), which represents a threshold that a human can perceive the depth difference between objects, we modify the depth image such that neighboring objects in the depth image can have a depth value difference of at least the JNDD. This modification is modeled vi

In this paper, we propose a new sharpness enhancement algorithm for stereo images. Although the stereo image and its applications are becoming increasingly prevalent, there has been very limited research on specialized image enhancement solutions for stereo images. Recently, a binocular just-noticeable-difference (BJND) model that describes the sensitivity of the human visual system to luminance changes in stereo images has been presented. We introduce a novel application of the BJND model for t

In this letter, we propose a new global contrast enhancement algorithm using the histograms of color and depth images. On the basis of the histogram-modification framework, the color and depth image histograms are first partitioned into sub-intervals using the Gaussian mixture model. The positions partitioning the color histogram are then adjusted such that spatially neighboring pixels with the similar intensity and depth values can be grouped into the same sub-interval. By estimating the mappin

Generative adversarial networks (GAN) have been successfully used in many image restoration tasks, including image denoising, super‐resolution, and compression artifact reduction. By fully exploiting its characteristics, state‐of‐the‐art image restoration techniques can be used to generate images with photorealistic details. However, there are many applications that require faithful rather than visually appealing image reconstruction, such as medical imaging, surveillance, and video coding. We f

The just noticeable depth difference (JNDD) describes the threshold of human perception of the difference in the depth. In flat-panel-based three-dimensional (3-D) displays, the JNDD is typically measured by changing the depth difference between displayed image objects until the difference is perceivable. However, not only the depth, but also the perceived size changes when the depth difference increases. In this paper, we present a modified JNDD measurement method that adjusts the physical size

Aspergillus causes a variety of clinical syndromes in the lung including tracheobronchial aspergillosis, invasive aspergillosis, chronic necrotizing pulmonary aspergillosis, allergic bronchopulmonary aspergillosis, and aspergilloma. Aspergilloma usually results from ingrowths of colonized Aspergillus in damaged bronchial tree, pulmonary cyst or cavities of patients with underlying lung diseases. There are a few reports on endobronchial aspergilloma without underlying pulmonary lesion. We have ex

<para xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> In this letter, we present a novel image restoration algorithm to deblur the image without estimating the image blur. The proposed algorithm performs deblurring by merging differently blurred multiple images in the spectrum domain using the fuzzy projection onto convex sets (POCS). Experimental results demonstrate that the merged single image contains much less blur than the multiple blurred images.

Recently, owing to the development of information technology, there have been many changes in learning activities and equipment. For instance, compared with traditional textbook-based learning, e-learning has freed learners from spatial-temporal restrictions, and other educational media are replacing textbooks. Specifically, educational videos have become very popular, as they are effective at conveying their content or meaning. Furthermore, their accessibility has been improved because of the e

As a variety of video surveillance devices such as CCTV, drones, and car dashboard cameras have become popular, numerous studies have been conducted regarding the effective enforcement of security and surveillance based on video analysis. In particular, in car-related surveillance, car tracking is the most challenging task. One early approach to accomplish such a task was to analyze frames from different video sources separately. Considering the shooting range of the bulk of video devices, the o

Deep-learning-based survival prediction can assist doctors by providing additional information for diagnosis by estimating the risk or time of death. The former focuses on ranking deaths among patients based on the Cox model, whereas the latter directly predicts the survival time of each patient. However, it is observed that survival time prediction for the patients, particularly with close observation times, possibly has incorrect orders, leading to low prediction accuracy. Therefore, in this p