• Journal of the Korean Society of Radiology
• /
• v.17 no.3
• /
• pp.359-365
• /
• 2023

In order to satisfy the requirements of dynamic X-ray imaging with high frame rate and low image lag, minimizing parasitic capacitance in photodiode and overlapped electrodes in pixels is critically required. This study presents duoPIX^TM dynamic X-ray imaging sensor composing of readout thin film transistor, reset thin film transistor and photodiode in a pixel. Furthermore, dynamic X-ray detector using duoPIX^TM imaging sensor was manufactured and evaluated its X-ray imaging performances such as frame rate, sensitivity, noise, MTF and image lag. duoPIX^TM dynamic X-ray detector has 150 × 150 mm² imaging area, 73 um pixel pitch, 2048 × 2048 matrix resolution(4.2M pixels) and maximum 50 frames per second. By means of comparison with conventional dynamic X-ray detector, duoPIX^TM dynamic X-ray detector showed overall better performances than conventional dynamic X-ray detector as shown in the previous study.

• Proceedings of the Korean Society of Medical Physics Conference
• /
• 2002.09a
• /
• pp.389-392
• /
• 2002

Digital radiography (DR) is being developed for numerous applications in medical imaging. For understanding DR image, it is necessary to comprehend DR responses to X-ray in terms of absorbed energy. This study reports on the relationship of absorbed energy in the scintillator vs. pixel value of detector. Pixel value and exposure were measured from 50 kVp to 120 kVp until the detector was saturated. For representing radiation produced at the X-ray tube, we used program Srs-78 and compared experimental exposure with calculated exposure. Absorbed energy was acquired using spectrum and we got the relation between the two values.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.11 no.1
• /
• pp.360-373
• /
• 2017

This paper presents a novel digital video steganalysis scheme against the spatial domain video steganography technology based on a spatial temporal detector (ST_D) that considers both spatial and temporal redundancies of the video sequences simultaneously. Three descriptors are constructed on XY, XT and YT planes respectively to depict the spatial and temporal relationship between the current pixel and its adjacent pixels. Considering the impact of local motion intensity and texture complexity on the histogram distribution of three descriptors, each frame is segmented into non-overlapped blocks that are $8{\times}8$ in size for motion and texture analysis. Subsequently, texture and motion factors are introduced to provide reasonable weights for histograms of the three descriptors of each block. After further weighted modulation, the statistics of the histograms of the three descriptors are concatenated into a single value to build the global description of ST_D. The experimental results demonstrate the great advantage of our features relative to those of the rich model (RM), the subtractive pixel adjacency model (SPAM) and subtractive prediction error adjacency matrix (SPEAM), especially for compressed videos, which constitute most Internet videos.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.12 no.8
• /
• pp.3873-3887
• /
• 2018

In this paper, we propose a novel method to recover images corrupted by impulse noise. The proposed method uses two stages: noise detection and filtering. In the first stage, we use pixel values, rank-ordered logarithmic difference values, and median values to train a neural-network-based impulse noise detector. After training, we apply the network to detect noisy pixels in images. In the next stage, we use group-based weighted couple sparse representation to filter the noisy pixels. During this second stage, conventional methods generally use only clean pixels to recover corrupted pixels, which can yield unsuccessful dictionary learning if the noise density is high and the number of useful clean pixels is inadequate. Therefore, we use reconstructed pixels to balance the deficiency. Experimental results show that the proposed noise detector has better performance than the conventional noise detectors. Also, with the information of noisy pixel location, the proposed impulse-noise removal method performs better than the conventional methods, through the recovered images resulting in better quality.

• Korean Journal of Geomatics
• /
• v.4 no.1
• /
• pp.1-8
• /
• 2004

In the middle-resolution remote sensing, the Ground Sampled Distance (GSD) that the detector senses and samples is generally larger than the actual size of the objects (or materials) of interest, and so several objects are embedded in a single pixel. In this case, as it is impossible to detect these objects by the conventional spatial-based image processing techniques, it has to be carried out at sub-pixel level through spectral properties. In this paper, we explain the sub-pixel analysis algorithm, also known as the Linear Spectral Mixing (LSM) model, which has been experimented using the Hyperion data. To find Endmembers used as the prior knowledge for LSM model, we applied the concept of the convex geometry on the two-dimensional scatter plot. The Atmospheric Correction and Minimum Noise Fraction techniques are presented for the pre-processing of Hyperion data. As LSM model is the simplest approach in sub-pixel analysis, the results of our experiment is not good. But we intend to say that the sub-pixel analysis shows much more information in comparison with the image classification.

• Proceedings of the Korean Nuclear Society Conference
• /
• 2005.10a
• /
• pp.729-730
• /
• 2005

• Journal of the Korea Institute of Military Science and Technology
• /
• v.23 no.6
• /
• pp.609-617
• /
• 2020

Non-destructive inspection using X-rays is used as a method to check the inside of products. In order to accurately inspect, a X-ray image requires a higher spatial resolution. However, the reduction in pixel size of the X-ray detector, which determines the spatial resolution, is time-consuming and expensive. In this regard, a DMM has been proposed to obtain an improved spatial resolution using the same X-ray detector. However, this has a limitation that the motion blur phenomenon, which is a decrease in spatial resolution. In this paper, motion blur was removed by applying Non-Blind Deconvolution to the DMM image, and the increase in spatial resolution was confirmed. DMM and Non-Blind Deconvolution were sequentially applied to X-ray images, confirming 62 % MTF value by an additional 29 % over 33 % of DMM only. In addition, SSIM and PSNR were compared to confirm the similarity to the 1/2 pixel detector image through 0.68 and 33.21 dB, respectively.

• Proceedings of the Korean Society of Medical Physics Conference
• /
• 2002.09a
• /
• pp.373-375
• /
• 2002

4D CT is a dynamic volume imaging system of moving organs with an image quality comparable to conventional CT, and is realized with continuous and high-speed cone-beam CT. In order to realize 4D CT, we have developed a novel 2D detector on the basis of the present CT technology, and mounted it on the gantry frame of the state-of-the-art CT-scanner. In the present report we describe the design of the first model of 4D CT-scanner as well as the early results of performance test. The x-ray detector for the 4D CT-scanner is a discrete pixel detector in which pixel data are measured by an independent detector element. The numbers of elements are 912 (channels) ${\times}$ 256 (segments) and the element size is approximately 1mm ${\times}$ 1mm. Data sampling rate is 900views(frames)/sec, and dynamic range of A/D converter is 16bits. The rotation speed of the gantry is l.0sec/rotation. Data transfer system between rotating and stationary parts in the gantry consists of laser diode and photodiode pairs, and achieves net transfer speed of 5Gbps. Volume data of 512${\times}$512${\times}$256 voxels are reconstructed with FDK algorithm by parallel use of 128 microprocessors. Normal volunteers and several phantoms were scanned with the scanner to demonstrate high image quality.

• Ocean Systems Engineering
• /
• v.2 no.2
• /
• pp.137-145
• /
• 2012

Recent developments in underwater image recognition methods have received large attention by the ocean engineering researchers. In this paper, an improved bi-dimensional empirical mode decomposition (BEMD) approach is employed to decompose the given underwater image into intrinsic mode functions (IMFs) and residual. We developed a joint algorithm based on BEMD and Canny operator to extract multi-pixel edge features at multiple scales in IMFs sub-images. So the multiple pixel edge extraction is an advantage of our approach; the other contribution of this method is the realization of the bi-dimensional sifting process, which is realized utilizing regional-based operators to detect local extreme points and constructing radial basis function for curve surface interpolation. The performance of the multi-pixel edge extraction algorithm for processing underwater image is demonstrated in the contrast experiment with both the proposed method and the phase congruency edge detection.

• Proceedings of the KSRS Conference
• /
• 2006.03a
• /
• pp.315-318
• /
• 2006

Pushbroom 방식의 CCD 영상에서 발생하는 pixel들 사이의 Non-uniformity 원인은 CCD pixel 면적의 차이, Dark current 영향, Output amplifier 차이, input radiance의 차이 등과 같은 CCD의 특성에 의해 발생하게 되며, CCD의 특성에 의해 발생되는 pixel사이의 상대복사량 차이인 Non-uniformity errors은 위성영상에서 줄무늬의 일차적 원인이 된다. 이러한 CCD의 상대복사보정을 위해서는 일차적으로 CCD의 특성을 잘 파악할 수 있는 지상에서 보정 값이 계산되어져야 하며 위성발사 후 보정 값이 다시 update 되어야 한다. 본 연구에서는 다목적실용위성2호의 상대복사보정을 위한 준비로서, 지상에서 만들어진 MSC CCD PAN1 영상과 Pushbroom 방식의 다목적실용위성1호 영상을 시험자료로 이용하여 pixel 사이의 줄무늬를 제거하기 위한 상대복사보정을 수행하였다.