Browsing by Author "Lin, Meng-Chun"

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A Content-Motion-Aware Motion Estimation for Quality-Stationary Video Coding
(2010)
Lin, Meng-Chun
;
Dung, Lan-Rong
;
電控工程研究所
;
Institute of Electrical and Control Engineering
The block-matching motion estimation has been aggressively developed for years. Many papers have presented fast block-matching algorithms (FBMAs) for the reduction of computation complexity. Nevertheless, their results, in terms of video quality and bitrate, are rather content-varying. Very few FBMAs can result in stationary or quasistationary video quality for different motion types of video content. Instead of using multiple search algorithms, this paper proposes a quality-stationary motion estimation with a unified search mechanism. This paper presents a content-motion-aware motion estimation for quality-stationary video coding. Under the rate control mechanism, the proposed motion estimation, based on subsample approach, adaptively adjusts the subsample ratio with the motion-level of video sequence to keep the degradation of video quality low. The proposed approach is a companion for all kinds of FBMAs in H. 264/AVC. As shown in experimental results, the proposed approach can produce stationary quality. Comparing with the full-search block-matching algorithm, the quality degradation is less than 0.36 dB while the average saving of power consumption is 69.6%. When applying the proposed approach for the fast motion estimation (FME) algorithm in H. 264/AVC JM reference software, the proposed approach can save 62.2% of the power consumption while the quality degradation is less than 0.27 dB.
A Subsample-Based Low-Power Image Compressor for Capsule Gastrointestinal Endoscopy
(2011)
Lin, Meng-Chun
;
Dung, Lan-Rong
;
電控工程研究所
;
Institute of Electrical and Control Engineering
In the design of capsule endoscope, the trade-offs between battery-life and video-quality is imperative. Typically, the resolution of capsule gastrointestinal (GI) image is limited for the power consumption and bandwidth of RF transmitter. Many fast compression algorithms for reducing computation load; however, they may result in a distortion of the original image, which is not suitable for the use of medical care. This paper presents a novel image compression for capsule gastrointestinal endoscopy, called GICam-II, motivated by the reddish feature of GI image. The reddish feature makes the luminance or sharpness of GI image sensitive to the red component as well as the green component. We focus on a series of mathematical statistics to systematically analyze the color sensitivity in GI images from the RGB color space domain to the two-dimensional discrete-cosine-transform spatial frequency domain. To reduce the compressed image size, GICam-II downsamples the blue component without essential loss of image detail and also subsamples the green component from the Bayer-patterned image. From experimental results, the GICam-II can significantly save the power consumption by 38.5% when compared with previous one and 98.95% when compared with JPEG compression, while the average peak signal-to-noise ratio of luminance (PSNRY) is 40.73 dB.
A subsample-based motion estimation for quality-stationary video coding
(2006)
Lin, Meng-Chun
;
Dung, Lan-Rong
;
Lin, Hsuan-Po
;
交大名義發表
;
National Chiao Tung University
The block-matching motion estimation has been aggressively developed for years. Many papers have presented fast block-matching algorithms (FBMAs) for the reduction of computation complexity. Nevertheless, their results, in terms of video quality and bitrate, are rather content-varying. Very few FBMAs can result in stationary or quasi-stationary video quality or bitrate for different types of video content. This paper presents a content-motion-aware motion estimation for quality-stationary video coding. By adaptively specifying the subsample ratio, the proposed algorithm can adjust the computational load for acceptable quality loss under the rate control mechanism. As the simulation result, the proposed algorithm can produce stationary quality at the PSNR of 036 dB for a given bitrate while saving about 69.6% power consumption.
An ultra-low-power image compressor for capsule endoscope
(2006-02-25)
Lin, Meng-Chun
;
Dung, Lan-Rong
;
Weng, Ping-Kuo
;
電控工程研究所
;
Institute of Electrical and Control Engineering
Background: Gastrointestinal (GI) endoscopy has been popularly applied for the diagnosis of diseases of the alimentary canal including Crohn's Disease, Celiac disease and other malabsorption disorders, benign and malignant tumors of the small intestine, vascular disorders and medication related small bowel injury. The wireless capsule endoscope has been successfully utilized to diagnose diseases of the small intestine and alleviate the discomfort and pain of patients. However, the resolution of demosaicked image is still low, and some interesting spots may be unintentionally omitted. Especially, the images will be severely distorted when physicians zoom images in for detailed diagnosis. Increasing resolution may cause significant power consumption in RF transmitter; hence, image compression is necessary for saving the power dissipation of RF transmitter. To overcome this drawback, we have been developing a new capsule endoscope, called GICam. Methods: We developed an ultra-low-power image compression processor for capsule endoscope or swallowable imaging capsules. In applications of capsule endoscopy, it is imperative to consider battery life/performance trade-offs. Applying state-of-the-art video compression techniques may significantly reduce the image bit rate by their high compression ratio, but they all require intensive computation and consume much battery power. There are many fast compression algorithms for reducing computation load; however, they may result in distortion of the original image, which is not good for use in the medical care. Thus, this paper will first simplify traditional video compression algorithms and propose a scalable compression architecture. Conclusion: As the result, the developed video compressor only costs 31 K gates at 2 frames per second, consumes 14.92 mW, and reduces the video size by 75% at least.
On VLSI design of rank-order filtering using DCRAM architecture
(2008-02-01)
Lin, Meng-Chun
;
Dung, Lan-Rong
;
電控工程研究所
;
Institute of Electrical and Control Engineering
This paper addresses on VLSI design of rank-order filtering (ROF) with a maskable memory for real-time speech and image processing applications. Based on a generic bit-sliced ROF algorithm, the proposed design uses a special-defined memory, called the dual-cell random-access memory (DCRAM), to realize major operations of ROF: threshold decomposition and polarization. Using the memory-oriented architecture, the proposed ROF processor can benefit from high flexibility, low cost and high speed. The DCRAM can perform the bit-sliced read, partial write, and pipelined processing. The bit-sliced read and partial write are driven by maskable registers. With recursive execution of the bit-slicing read and partial write, the DCRAM can effectively realize ROF in terms of cost and speed. The proposed design has been implemented using TSMC 0.18 mu m, 1P6M technology. As shown in the result of physical implementation, the core size is 356.1 x 427.7 mu m(2) and the VLSI implementation of ROF can operate at 256 MHz for 1.8 V supply. (C) 2007 Elsevier B.V. All rights reserved.
Two-Step Windowing Technique for Wide Range Motion Estimation
(2008)
Lin, Meng-Chun
;
Dung, Lan-Rong
;
電控工程研究所
;
Institute of Electrical and Control Engineering
This paper presents a memory-efficient motion estimation (ME) technique for high-resolution video compression. The main objective is to reduce the external memory access, especially for limited local memory resource. The key to reduce the memory accesses is based on center-biased algorithm in that the center-biased algorithm performs the motion vector (MV) searching with the minimum search data. While considering the data reusability, the proposed two-step windowing approaches use the secondary windowing as an option per searching necessity. The proposed techniques can save up to 81% of external memory bandwidth and require only 135 MBytes/sec, while the quality degradation is less than 0.2 dB for 720p HDTV clips coded at 8 Mbits/sec.
Wide-Range Motion Estimation Architecture with Dual Search Windows for High Resolution Video Coding
(2008-12-01)
Dung, Lan-Rong
;
Lin, Meng-Chun
;
電控工程研究所
;
Institute of Electrical and Control Engineering
This paper presents a memory-efficient motion estimation (ME) technique for high-resolution video compression. The main objective is to reduce the external memory access, especially for limited local memory resource. The reduction of memory access can successfully save the notorious power consumption. The key to reduce the memory accesses is based on center-biased algorithm in that the center-biased algorithm performs the motion vector (MV) searching with the minimum search data. While considering the data reusability, the proposed dual-search-windowing (DSW) approaches use the secondary windowing as an option per searching necessity. By doing so, the loading of search windows can be alleviated and hence reduce the required external memory bandwidth. The proposed techniques can save up to 81% of external memory bandwidth and require only 135 MBytes/sec, while the quality degradation is less than 0.2 dB for 720 p HDTV clips coded at 8 Mbits/sec.