• Journal of the Institute of Convergence Signal Processing
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• v.8 no.4
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• pp.237-243
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• 2007

In this paper, we propose the Real-time Dead-Pixel Detection and Compensation System for mobile camera and its hardware architecture. The CMOS image sensors as image input devices are becoming popular due to the demand for miniaturized, low-power and cost-effective imaging systems. However a conventional Dead-Pixel Detection Algorithm is disable to detect neighboring dead pixels and it degrades image quality by wrong detection and compensation. To detect dead pixels the proposed system is classifying dead pixels into Hot pixel and Cold pixel. Also, the proposed algorithm is processing line-detector and $5{\times}5$ window-detector consecutively. The line-detector and window-detector can search dead pixels by using one-dimensional(only horizontal) method in low frequency area and two-dimensional(vertical and diagonal) method in high frequency area, respectively. The experimental result shows that it can detect 99% of dead pixels. It was designed in Verilog hardware description language and total gate count is 23K using TSMC 0.25um ASIC library.

• The KIPS Transactions:PartA
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• v.12A no.6 s.96
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• pp.523-530
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• 2005

When a PCI 2.2 bus master requests data using Memory Read command, a target device may hold PCI bus without data to be transferred for long time because a target device needs time to prepare data infernally. Because the usage efficiency of the PCI bus and the data transfer efficiency are decreased due to this situation, the PCI specification recommends to use the Delayed Transaction mechanism to improve the system performance. But the mechanism cann't fully improve performance because a target device doesn't know the exact size of prefetched data. In the previous work, we propose a new method called Prefetch Request when a bus master intends to read data from the target device. In this paper, we design PCI 2.2 controller and local device that support the proposed method. The designed PCI 2.2 controller has simple local interface and it is used to convert the PCI protocol into the local protocol. So the typical users, who don't know the PCI protocol, can easily design the PCI target device using the proposed PCI controller. We propose the basic behavioral verification, hardware design verification, and random test verification to verify the designed hardware. We also build the test bench and define assembler instructions. And we propose random testing environment, which consist of reference model, random generator ,and compare engine, to efficiently verify corner case. This verification environment is excellent to find error which is not detected by general test vector. Also, the simulation under the proposed test environment shows that the proposed method has the higher data transfer efficiency than the Delayed Transaction about $9\%$.

• Investigative Magnetic Resonance Imaging
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• v.8 no.1
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• pp.42-49
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• 2004

Purpose : The quantization noise in magnetic resonance imaging (MRI) systems is analyzed. The signal-to-quantization noise ratio (SQNR) in the reconstructed image is derived from the level of quantization in the signal in spatial frequency domain. Based on the derived formula, the SQNRs in various main magnetic fields with different receiver systems are evaluated. From the evaluation, the quantization noise could be a major noise source determining overall system signal-to-noise ratio (SNR) in high field MRI system. A few methods to reduce the quantization noise are suggested. Materials and methods : In Fourier imaging methods, spin density distribution is encoded by phase and frequency encoding gradients in such a way that it becomes a distribution in the spatial frequency domain. Thus the quantization noise in the spatial frequency domain is expressed in terms of the SQNR in the reconstructed image. The validity of the derived formula is confirmed by experiments and computer simulation. Results : Using the derived formula, the SQNRs in various main magnetic fields with various receiver systems are evaluated. Since the quantization noise is proportional to the signal amplitude, yet it cannot be reduced by simple signal averaging, it could be a serious problem in high field imaging. In many receiver systems employing analog-to-digital converters (ADC) of 16 bits/sample, the quantization noise could be a major noise source limiting overall system SNR, especially in a high field imaging. Conclusion : The field strength of MRI system keeps going higher for functional imaging and spectroscopy. In high field MRI system, signal amplitude becomes larger with more susceptibility effect and wider spectral separation. Since the quantization noise is proportional to the signal amplitude, if the conversion bits of the ADCs in the receiver system are not large enough, the increase of signal amplitude may not be fully utilized for the SNR enhancement due to the increase of the quantization noise. Evaluation of the SQNR for various systems using the formula shows that the quantization noise could be a major noise source limiting overall system SNR, especially in three dimensional imaging in a high field imaging. Oversampling and off-center sampling would be an alternative solution to reduce the quantization noise without replacement of the receiver system.