• Proceedings of the KSRS Conference
• /
• v.1
• /
• pp.508-511
• /
• 2006

Generally, stereo pair images are necessary for 3D viewing. In the absence of quality stereo-pair images, it is possible to synthesize a stereo-mate suitable for 3D viewing with a single image and a depth-map. In remote sensing, DEM is usually used as a depth-map. In this paper, LiDAR data was used instead of DEM to make a stereo pair from a single aerial photo. Each LiDAR point was assigned a brightness value from the original single image by registration of the image and LiDAR data. And then, imaginary exposure station and image plane were assumed. Finally, LiDAR points with already-assigned brightness values were back-projected to the imaginary plane for synthesis of a stereo-mate. The imaginary exposure station and image plane were determined to have only a horizontal shift from the original image's exposure station and plane. As a result, the stereo-mate synthesized in this paper fulfilled epipolar geometry and yielded easily-perceivable 3D viewing effect together with the original image. The 3D viewing effect was tested with anaglyph at the end.

• Journal of radiological science and technology
• /
• v.13 no.2
• /
• pp.15-20
• /
• 1990

In clinical fields, single screen-film system will be generalized according to high speed and high image qualify of intensifying screen film system in future. In single screen-film system, for imaging the best image, we must choice good film according to speed and gredient. Double screen-film system will be replaced single screen film system in general radiography. Author has thought that single screen film system will be developed new diagnosis area according to X-Ray films.

• Journal of Institute of Control, Robotics and Systems
• /
• v.12 no.7
• /
• pp.686-692
• /
• 2006

This paper shows the calculation of 3D geometric information such as height, direction and distance under the constraints of a catadioptric camera system. The catadioptric camera system satisfies the single viewpoint constraints adopting hyperboloidal mirror. To calculate the 3D information with a single omni-directional image, the points are assumed to lie in perpendicular to the ground. The infinite plane is also detected as a circle from the structure of the mirror and camera. The analytic experiments verify the correctness of theory using real images taken in indoor environments like rooms or corridors. Thus, the experimental results show the applicability to calculate the 3D geometric information using single omni-directional images.

• Journal of Institute of Control, Robotics and Systems
• /
• v.19 no.11
• /
• pp.955-959
• /
• 2013

It is possible to obtain an omnidirectional stereo image via a single camera by using a catadioptric approach with a convex mirror and concave lens. In order to measure three-dimensional distance using the imaging system, the optical parameters of the system are required. In this paper, a calibration procedure to extract the parameters of the imaging system is described. Based on the parameters, experiments are carried out to verify the performance of the three-dimensional distance measurement of a single camera omnidirectional stereo imaging system.

• Nuclear Engineering and Technology
• /
• v.53 no.7
• /
• pp.2341-2347
• /
• 2021

Because single-photon emission computed tomography (SPECT) is one of the widely used nuclear medicine imaging systems, it is extremely important to acquire high-quality images for diagnosis. In this study, we designed a super-resolution (SR) technique using dense block-based deep convolutional neural network (CNN) and evaluated the algorithm on real SPECT phantom images. To acquire the phantom images, a real SPECT system using a^99mTc source and two physical phantoms was used. To confirm the image quality, the noise properties and visual quality metric evaluation parameters were calculated. The results demonstrate that our proposed method delivers a more valid SR improvement by using dense block-based deep CNNs as compared to conventional reconstruction techniques. In particular, when the proposed method was used, the quantitative performance was improved from 1.2 to 5.0 times compared to the result of using the conventional iterative reconstruction. Here, we confirmed the effects on the image quality of the resulting SR image, and our proposed technique was shown to be effective for nuclear medicine imaging.

• Proceedings of the KIEE Conference
• /
• 1998.11b
• /
• pp.511-513
• /
• 1998

This paper describes a full color stereoscopic video display system using a LCD shutter. Human apprehends the world with a natural stereo vision. The left eye sees through a slightly different perspective from the right eye; proposed vision system combines two images into a single image that has stereo depth. That is, when the left image is on the screen, the left shutter opens and the right shutter closes - and vice versa. The LCD shutter channels the left image to the left eye, and the right image to the right eye. The brain then fuses the stereo pair into a single high-resolution, flicker-free 3D image. The designed vision system is a real-time system that shows stereoscopic images without the loss of image information from video cameras.

• IEIE Transactions on Smart Processing and Computing
• /
• v.3 no.6
• /
• pp.382-387
• /
• 2014

A computational approach to depth estimations using a color over lapped integral imaging system is presented. The proposed imaging system acquires multiple color images simultaneously through a single lens with an array of multiple pinholes that are distributed around the optical axis. This paper proposes a computational model of the relationship between the real distance of an object and the disparity among different color images. The proposed model can serve as a computational basis of a single camera-based depth estimation.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.8 no.3
• /
• pp.1058-1070
• /
• 2014

There are two major ways to implement depth estimation, multiple image depth estimation and single image depth estimation, respectively. The former has a high hardware cost because it uses multiple cameras but it has a simple software algorithm. Conversely, the latter has a low hardware cost but the software algorithm is complex. One of the recent trends in this field is to make a system compact, or even portable, and to simplify the optical elements to be attached to the conventional camera. In this paper, we present an implementation of depth estimation with a single image using a graphics processing unit (GPU) in a desktop PC, and achieve real-time application via our evolutional algorithm and parallel processing technique, employing a compute shader. The methods greatly accelerate the compute-intensive implementation of depth estimation with a single view image from 0.003 frames per second (fps) (implemented in MATLAB) to 53 fps, which is almost twice the real-time standard of 30 fps. In the previous literature, to the best of our knowledge, no paper discusses the optimization of depth estimation using a single image, and the frame rate of our final result is better than that of previous studies using multiple images, whose frame rate is about 20fps.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.10 no.3
• /
• pp.1182-1194
• /
• 2016

The single image dehazing algorithm in existence can satisfy the demand only for improving either the effectiveness or efficiency. In order to solve the problem, a novel variational framework for single image dehazing based on restoration is proposed. Firstly, the initial atmospheric scattering model is transformed to meet the kimmel's Retinex variational model. Then, the green light component of image is considered as an input of the variational framework, which is generated by the sensitivity of green wavelength. Finally, the atmospheric transmission map is achieved by multi-resolution pyramid reduction to improve the visual effect of the results. Experimental results demonstrate that the proposed method can remove haze effectively with less memory consumption.

• Journal of Electrical Engineering and Technology
• /
• v.10 no.4
• /
• pp.1886-1898
• /
• 2015

In today’s era of advanced technological developments, the threats to the authenticity and integrity of digital images, in a nutshell, the threats to the Image Forensics Research communities have also increased proportionately. This happened as even for the ‘non-expert’ forgers, the availability of image processing tools has become a cakewalk. This image forgery poses a great problem for judicial authorities in any context of trade and commerce. Block matching based image cloning detection system is widely researched over the last 2-3 decades but this was discouraged by higher computational complexity and more time requirement at the algorithm level. Thus, for reducing time need, various dimension reduction techniques have been employed. Since a single technique cannot cope up with all the transformations like addition of noise, blurring, intensity variation, etc. we employ multiple techniques to a single image. In this paper, we have used Fuzzy logic approach for decision making and getting a global response of all the techniques, since their individual outputs depend on various parameters. Experimental results have given enthusiastic elicitations as regards various transformations to the digital image. Hence this paper proposes Fuzzy based cloning detection and classification system. Experimental results have shown that our detection system achieves classification accuracy of 94.12%. Detection accuracy (DAR) while in case of 81×81 sized copied portion the maximum accuracy achieved is 99.17% as regards subjection to transformations like Blurring, Intensity Variation and Gaussian Noise Addition.