• Journal of Institute of Control, Robotics and Systems
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• v.12 no.4
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• pp.364-370
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• 2006

Optical coherence tomography (OCT) is high resolution medical imaging system which is obtaining image inside biological objects with non-destructive method. OCT system is based on Michelson interferometer with a reciprocating mirror in the reference arm and a biological object in the sample arm. The obtained OCT image suffers from a granular or mottled image, called speckle. Speckle is caused by random interferences between reflected coherence waves. In this paper, we propose effective speckle reduction method that uses wavelet transform. With wavelet domain image, sub-windowing and thresholding are performed. Finally, speckle reduction experiments for Misgurnus mizolepis skin and rat eye images are shown.

• Journal of Institute of Control, Robotics and Systems
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• v.20 no.6
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• pp.657-662
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• 2014

Usually, spatial information can be incorporated into histograms by taking histograms of a multiresolution image. For these reasons, many researchers are interested in multiresolution histogram processing. If the relation and sensitivity of the multiresolution images are well combined without loss of information, we can obtain satisfactory results in several fields of image processing including histogram equalization, specification and pattern matching. In this paper, we propose a multiresolution histogram specification method that improves the accuracy of histogram specification. The multiresolution decomposition technique is used in order to overcome the unique feature of a histogram specification affected by a quantization error of a digitalized image. The histogram specification is processed after the reduction of image resolution in order to enhance the accuracy of the results by histogram specification methods. The experimental results show that the proposed method enhances the accuracy of specification compared to conventional methods.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.18 no.2
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• pp.209-216
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• 2018

High-resolution satellite imagery is used in diverse fields such as meteorological observation, topography observation, remote sensing (RS), military facility monitoring and protection of cultural heritage. In satellite imagery, low-resolution imagery can take place depending on the conditions of hardware (e.g., optical system, satellite operation altitude, image sensor, etc.) even though the images were obtained from the same satellite imaging system. Once a satellite is launched, the adjustment of the imaging system cannot be done to improve the resolution of the degraded images. Therefore, there should be a way to improve resolution, using the satellite imagery. In this study, a super resolution (SR) algorithm was adopted to improve resolution, using such low-resolution satellite imagery. The SR algorithm is an algorithm which enhances image resolution by matching multiple low-resolution images. In satellite imagery, however, it is difficult to get several images on the same region. To take care of this problem, this study performed the SR algorithm by calibrating geometric changes on images after applying automatic extraction of feature points and projection transform. As a result, a clear edge was found just like the SR results in which feature points were manually obtained.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.10
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• pp.4948-4967
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• 2017

On mobile devices, image sequences are widely used for multimedia applications such as computer vision, video enhancement, and augmented reality. However, the real-time processing of mobile devices is still a challenge because of constraints and demands for higher resolution images. Recently, heterogeneous computing methods that utilize both a central processing unit (CPU) and a graphics processing unit (GPU) have been researched to accelerate the image sequence processing. This paper deals with various optimizing techniques such as parallel processing by the CPU and GPU, distributed processing on the CPU, frame buffer object, and double buffering for parallel and/or distributed tasks. Using the optimizing techniques both individually and combined, several heterogeneous computing structures were implemented and their effectiveness were analyzed. The experimental results show that the heterogeneous computing facilitates executions up to 3.5 times faster than CPU-only processing.

• Proceedings of the KIEE Conference
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• 2003.11c
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• pp.532-535
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• 2003

In this paper, we propose a new algorithm that can enhance the speed of template matching of hand vascular pattern person verification or recognition system. Various template matching algorithms have advantages in the matching accuracy, but most of the algorithms suffer from computational burden. To reduce the computational amount, with accuracy maintained, we propose following template matching scenario as follows. firstly, original hand vascular image is re-sampled in order to reduce spatial resolution. Secondly, reconstructed image is projected to vertical and horizontal direction, being converted to two one dimensional (1D) data. Thirdly, converted data is used to estimate spatial discrepancy between stored template image and target image. Finally, matching begins from where the estimated order is highest, and finishes when matching decision function is computed to be over certain threshold. We've applied the proposed algorithm to hand vascular pattern identification application for biometrics, and observed dramatic matching speed enhancement. This paper presents detailed explanation of the proposed algorithm and evaluation results.

• Journal of the Institute of Convergence Signal Processing
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• v.15 no.2
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• pp.24-29
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• 2014

Digital mammography is the most common technique for the early detection of breast cancer. To diagnose the breast cancer in early stages and treat efficiently, many image enhancement methods have been developed. This paper presents a multi-scale contrast enhancement method in the Laplacian pyramid for the digital mammogram. The proposed method decomposes the image into the contrast measures by the Gaussian and Laplacian pyramid, and the pyramid coefficients of decomposed multi-resolution image are defined as the frequency limited local contrast measures by the ratio of high frequency components and low frequency components. The decomposed pyramid coefficients are modified by the contrast measure for enhancing the contrast, and the final enhanced image is obtained by the composition process of the pyramid using the modified coefficients. The proposed method is compared with other existing methods, and demonstrated to have quantitatively good performance in the contrast measure algorithm.

• Journal of KIISE:Software and Applications
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• v.29 no.4
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• pp.235-247
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• 2002

For an efficient indexing and retrieval of digital video data, research on video caption extraction and recognition is required. This paper proposes methods for extracting artificial captions from video data and enhancing their image quality for an accurate Hangul and English character recognition. In the proposed methods, we first find locations of beginning and ending frames of the same caption contents and combine those multiple frames in each group by logical operation to remove background noises. During this process an evaluation is performed for detecting the integrated results with different caption images. After the multiple video frames are integrated, four different image enhancement techniques are applied to the image: resolution enhancement, contrast enhancement, stroke-based binarization, and morphological smoothing operations. By applying these operations to the video frames we can even improve the image quality of phonemes with complex strokes. Finding the beginning and ending locations of the frames with the same caption contents can be effectively used for the digital video indexing and browsing. We have tested the proposed methods with the video caption images containing both Hangul and English characters from cinema, and obtained the improved results of the character recognition.

• Journal of the Korean Society of Radiology
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• v.2 no.1
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• pp.23-29
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• 2008

The present study proposed a method that dissolves ultrasonographic images into multiple resolutions using wavelet conversion and a boundary detection filter and improves the quality of ultrasonographic images through boundary detection filtering. In order to reduce noises and strengthen edges, the proposed method adjusted selectivity coefficient by area step by step from a low resolution image obtained from wavelet converted images to a high resolution image and performed edge filtering in consideration of direction. Through this method, we generated a selective low pass filtering effect in areas except edges by decreasing the wavelet coefficient for pixels in spot areas, improved continuity by smoothing edges in the tangential direction, and enhanced contrast by thinning in the normal direction. Through an experiment, we compared the filtering method using a non linear anisotropic expansion model and the filtering method using wavelet contraction structure in single resolution.

• Imaging Science in Dentistry
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• v.47 no.3
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• pp.199-207
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• 2017

Purpose: Evaluation of alveolar bone is important in the diagnosis of dental diseases. The periodontal ligament space is difficult to clearly depict in cone-beam computed tomography images because the reconstruction filter conditions during image processing cause image blurring, resulting in decreased spatial resolution. We examined different reconstruction filters to assess their ability to improve spatial resolution and allow for a clearer visualization of the periodontal ligament space. Materials and Methods: Cone-beam computed tomography projections of 2 skull phantoms were reconstructed using 6 reconstruction conditions and then compared using the Thurstone paired comparison method. Physical evaluations, including the modulation transfer function and the Wiener spectrum, as well as an assessment of space visibility, were undertaken using experimental phantoms. Results: Image reconstruction using a modified Shepp-Logan filter resulted in better sensory, physical, and quantitative evaluations. The reconstruction conditions substantially improved the spatial resolution and visualization of the periodontal ligament space. The difference in sensitivity was obtained by altering the reconstruction filter. Conclusion: Modifying the characteristics of a reconstruction filter can generate significant improvement in assessments of the periodontal ligament space. A high-frequency enhancement filter improves the visualization of thin structures and will be useful when accurate assessment of the periodontal ligament space is necessary.

• Proceedings of the Optical Society of Korea Conference
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• 2002.07a
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• pp.246-247
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• 2002

OCT(Optical Coherence Tomography)는 실시간에 생체의 단면을 절개하지 않고도 고해상도의 단층 이미지를 얻을 수 있다는 장점을 지니고 있다. 이러한 면에서 OCT는 현재 사용되고 있는 여러 image modality들의 낮은 분해능을 해결할 수 있는 진보된 대안으로 각광을 받고 있다. 최근 OCT에서 가능한 이미지의 분해능은 수 $\mu$m 정도까지 보고되고 있다. (1) 이러한 OCT의 분해능은 사용하는 광원에 의해서 결정된다. (중략)