Sang Hoon Lee
Korea Advanced Institute of Science and Technology · 工学
研究室紹介
Professor Sang Hoon Lee's research lab specializes in perceptual video and image processing, with a strong focus on foveated imaging and compression techniques that leverage the nonuniform sensitivity of the human visual system. The lab develops advanced rate control algorithms and quality metrics—such as foveal signal-to-noise ratio (FSNR)—to optimize visual quality at reduced bit rates. It also explores applications in real-time video processing, unsupervised image classification using hierarchical clustering, and industrial parameter identification for electric machines. The lab’s work bridges human perception, signal processing, and practical system design for efficient multimedia and smart systems.
Research Overview
Research Output Trend
Figures are computed from collected data and may differ slightly.
Selected Papers
15Most image and video compression algorithms that have been proposed to improve picture quality relative to compression efficiency have either been designed based on objective criteria such as signal-to-noise-ratio (SNR) or have been evaluated, post-design, against competing methods using an objective sample measure. However, existing quantitative design criteria and numerical measurements of image and video quality both fail to adequately capture those attributes deemed important by the human vi
Previously, fovcated video compression algorithms have been proposed which, in certain applications, deliver high-quality video at reduced bit rates by seeking to match the nonuniform sampling of the human retina. We describe such a framework here where foveated video is created by a nonuniform filtering scheme that increases the compressibility of the video stream. We maximize a new foveal visual quality metric. the foveal signal-to-noise ratio (FSNR) to determine the best compression and rate
A new multistage method using hierarchical clustering for unsupervised image classification is presented. In the first phase, the multistage method performs segmentation using a hierarchical clustering procedure which confines merging to spatially adjacent clusters and generates an image partition such that no union of any neighboring segments has homogeneous intensity values. In the second phase, the segments resulting from the first stage are classified into a small number of distinct states b
This paper proposes an identification method for induction motor parameters at standstill using integral calculations. The rotor time constant and magnetizing inductance are identified. During the identification process, the induction motor to be tested is consistently excited according to a predetermined current reference. Using the predetermined current, the induction motor emulates the rated rotor flux and the rated slip condition, even at standstill. This method is based on an integral calcu
This paper explores the problem of communicating high-quality, foveated video streams in real time. Foveated video exploits the nonuniform resolution of the human visual system by preferentially allocating bits according to the proximity to assumed visual fixation points, thus delivering perceptually high quality at greatly reduced bandwidths. Foveated video streams possess specific data density properties that can be exploited to enhance the efficiency of subsequent video processing. Here, we e
This paper presents a novel high-speed low-complexity pipelined degree-computationless modified Euclidean (pDCME) algorithm architecture for high-speed RS decoders. The pDCME algorithm allows elimination of the degree-computation so as to reduce hardware complexity and obtain high-speed processing. A high-speed RS decoder based on the pDCME algorithm has been designed and implemented with 0.13-μm CMOS standard cell technology in a supply voltage of 1.1V. The proposed RS decoder operates at a clo
Fingerprint image-quality checking is one of the most important issues in fingerprint recognition because recognition is largely affected by the quality of fingerprint images. In the past, many related fingerprint-quality checking methods have typically considered the condition of input images. However, when using the preprocessing algorithm, ridge orientation may sometimes be extracted incorrectly. Unwanted false minutiae can be generated or some true minutiae may be ignored, which can also aff
The electrical, structural, and optical properties of GaAs grown by metalorganic chemical-vapor deposition using CCl4 have been studied and the growth rate reduction by CCl4 under various growth conditions has been investigated. Hole concentrations ranging from 2×1016 to 1.8×1020 cm−3 have been obtained by varying V/III ratio and growth temperature. From Hall, x-ray, and low-temperature photoluminescence measurements, a low compensation is ensured. A growth rate reduction up to 50% has been obse
A strategy for improving the sensitivity of a sensor for detecting CO and NH3 gases is presented herein. The gas sensor was fabricated from ZnO metal oxide semiconductor nanostructures grown via a vapor–liquid–solid process and decorated with α-Fe2O3 nanoparticles via a sol–gel process. The response was enhanced by the formation of an α-Fe2O3/ZnO n–n heterojunction and the growth of thinner wires. ZnO nanowires were grown on indium–tin–oxide glass electrodes using Sn as a catalyst for growth ins
A multistage hierarchical clustering technique, which is an unsupervised technique, has been proposed in this paper for classifying the hyperspectral data. The multistage algorithm consists of two stages. The "local" segmentor of the first stage performs region-growing segmentation by employing the hierarchical clustering procedure of CN-chain with the restriction that pixels in a cluster must be spatially contiguous. The "global" segmentor of the second stage, which has not spatial constraints