Tae-Chan Kim

New biometrics-acquisition method using time-of-flight depth camera

This paper introduces basic concept of biometrics acquisition method using time-of-flight (ToF) depth camera, taking the advantages of obtaining 3D data and near infrared (NIR) image simultaneously. This concept can be applied to various biometrics, such as touch-less or multimodal biometrics.

Mirrorless interchangeable-lens light field digital photography camera system

Camera system is expected to be evolved merging computational photography technique for having rich image information while maintaining image quality. The proposed camera system shows a newly designed system architecture scenario to have both high quality image performance and computational photography technique by combining digital single lens reflex (DSLR) based architecture and light field concept into a single integrated system. It starts from conventional digital DSLR architecture and enhances system features and reduces the problems with previous techniques.

Depth upsampling method using the confidence map for a fusion of a high resolution color sensor and low resolution time-of-flight depth sensor

This paper proposes a depth up-sampling method using the confidence map for a fusion of a high resolution color sensor and low resolution time-of-flight depth sensor. The confidence map represents the accuracy of depth depending on the reflectance of a measured object and is estimated with amplitude, offset, and reconstructed error of a received signal. The proposed method suppresses the depth artifacts that are caused by difference between low and high reflective materials on an object at a distance. Although the surface of an object is located at the same distance, the reflectance of small regions within the surface depends on constituent materials. Weighted filter generated by confidence map is added to the modified noise-aware filter for depth up-sampling that is proposed by Derek et al., and is adaptively selected. The proposed method consists of followings; the normalization, the reconstruction, the confidence map estimation, and the modified noise-aware filtering. In the normalization, amplitudes and offsets of received signals are calculated and received signals are normalized by those. The phase shifts are measured between transmitted and received signals. In the reconstruction, received signals are reconstructed using only the values of phase shifts and the reconstruction errors are calculated. The confidence map is estimated with amplitudes, offsets, and reconstruction errors. The coefficients of a modified noise-aware filter are adaptively selected by referring to the confidence map. The proposed method shows the enhanced results of removing depth artifacts in the experiments.

Image enhancement technique using color and edge features for mobile Systems

The paper provides a method of selectively controlling the strength of image noise reduction (NR) and sharpening in regions associated with specific colors that are visually impact on the human visual system. Since NR and sharpening operation can cause undesirable edge blurring or noise boosting in flat regions, the strength is adjusted according to the edge information. The proposed algorithm takes the following three stages: (i) color-based region classification, (ii) adaptive texture-based NR and sharpening, and (iii) H/W optimization for mobile image sensor compatibility. Experiments indicate that the proposed integrated algorithm platform provides significantly better results in terms of subjective visual quality.

Histogram based dynamic range compression method using simple locality consideration

In this paper, we present a local dynamic range compression method based on a computationally efficient histogram. The proposed method classifies input image into three regions using simple statistical analysis and generates scene adaptive tone mapping curves for each region. Moreover, dynamic range compression output is calculated based on the characteristic of local region and scene adaptive tone curves. Finally, we compare our method with other histogram based tone mapping approaches.

Flash image quality enhancement by compensating the quantity of flash light

The most of mobile phone camera are equipped with LED flash to acquire image under dark illuminant. However, the power of LED flash is not enough to illuminate the background area of scene as it becomes diminished in a distance. Moreover, mobile phone camera still suffers from low dynamic range. The facts bring unbalanced image in terms of brightness. To solve this problem, we propose method that estimates the intensity of flash light and compensate the difference of flash using flash and no-flash image pair. We confirmed the promising performance in an experiment using mobile phone camera.

CIS video panoramic image

The paper presented a technique of generating a CIS video panoramic image without rolling shutter distortion. When an image is captured by a rolling shutter camera in motion during a shuttering time, the captured image showed a distortion due to a rolling shutter mechanism and thus, a panoramic image stitched together with a sequence of those images also looked distorted. To solve the problem, a CIS distortion correction method is applied to a conventional video panoramic image method. The proposed CIS video panoramic image method estimates distortion parameters from two consecutive frames assuming that the global motion of two consecutive frames is affine and then, generates a distortion-free panoramic image while there are artifacts in a conventional video panoramic image.

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.