Design and implementation of a one-chip wireless camera device for a capsule endoscope

Itoh, Susumu; Kawahito, Shoji; Akahori, Tomoyuki; Terakawa, Susumu

doi:10.1117/12.587726

Cited by 6 publications

(7 citation statements)

References 2 publications

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“…The circuit in the dash-lined box is a comparator. The r [1] r [2] r [3] Carry Generator [2 ] Z b [3 ] FA/HA tree…”

Section: The Dual-cell Ram Architecture For Rank-order Filteringmentioning

confidence: 99%

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Study on Low-Power Image Processing for Gastrointestinal Endoscopy

Lin¹

2012

VLSI Design

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the task of smoothing or sharpening. Therefore, we need a flexible ROF hardware to arbitrarily select wanted rank values into the operation procedure of LUM filter and we have proposed an architecture based on a maskable memory for rank-order filtering. The maskable memory structure, called dual-cell random-access memory (DCRAM), is an extended SRAM structure with maskable registers and dual cells. This dissertation is the first literature using maskable memory to realize ROF. Driving by the generic rank-order filtering algorithm, the memory-based architecture features high degree of flexibility and regularity while the cost is low and the performance is high. This architecture can be applied for arbitrary ranks and a variety of ROF applications, including recursive and non-recursive algorithms. Except efficiently eliminating annoying impulsive noises and enhance sharpness for GI images, the processing speed of ROF can also meet the real-time image applications. 2. GICam image compressor 2.1 The review of GICam image compression algorithm Instead of applying state-of-the-art video compression techniques, we proposed a simplified image compression algorithm, called GICam. Traditional compression algorithms employ the YCbCr quantization to earn a good compression ratio while the visual distortion is minimized, based on the factors related to the sensitivity of the human visual system (HVS). However, for the sake of power saving, our compression rather uses the RGB quantization (15) to save the computation of demosaicking and color space transformation. As mentioned above, the advantage of applying RGB quantization is twofold: saving the power dissipation on preprocessing steps and reducing the computing load of 2-D DCT and quantization. Moreover, to reduce the hardware cost and quantization power dissipation, we have modified the RGB quantization tables and the quantization multipliers are power of two's. In GICam, the Lempel-Ziv (LZ) coding (18) is employed for the entropy coding. The reason we adopted LZ coding as the entropy coding, is because the LZ encoding does not need look-up tables and complex computation. Thus, the LZ encoding consumes less power and uses smaller silicon size than the other candidates, such as the Huffman encoding and the arithmetic coding. The target compression performance of the GICam image compression is to reduce image size by at least 75%. To meet the specification, given the quantization tables, we exploited the cost-optimal LZ coding parameters to meet the compression ratio requirement by simulating with twelve tested endoscopic pictures shown in Fig.3. When comparing the proposed image compression with the traditional one in (11), the power consumption of GICam image compressor can save 98.2% because of the reduction of memory requirement. However, extending the utilization of battery life for a capsule endoscope remains an important issue. The memory access dissipates the most power in GICam image compression. Therefore, in order to achieve the target of extending the battery li...

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“…The circuit in the dash-lined box is a comparator. The r [1] r [2] r [3] Carry Generator [2 ] Z b [3 ] FA/HA tree…”

Section: The Dual-cell Ram Architecture For Rank-order Filteringmentioning

confidence: 99%

“…Finally, we can implement the 2-D RMF as the block diagram illustrated in Fig.35. Given a 2-D 3 × 3 RMF application, the optimized reservation table can be scheduled as x (1,3) x (2,3) Address Data Field ...…”

Section: -D Recursive Median Filtermentioning

confidence: 99%

Study on Low-Power Image Processing for Gastrointestinal Endoscopy

Lin¹

2012

VLSI Design

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“…To further analyze the chrominance distributions and variations in the RGB color space for each tested GI image, two quantitative indexes are used to quantify these effects. The first index is to calculate the average distances between total pixels and the maximum primary colors in each GI image, and the calculations are formulated as (1), (2), and (3). First, (1) defines the average distance between total pixels and the most red color (R), in which R(i, j) means the value of red component of one GI image at (i, j) position and the value of most red color (R max ) is 255.…”

Section: The Distributions Of Primary Colors In the Rgb Colormentioning

confidence: 99%

“…The wired active endoscopy can enable efficient diagnosis based on real images and biopsy samples; however, it causes discomfort for the patients to push flexible, relatively bulky cables into the digestive tube. To relief the patients' discomfort, wireless passive capsule endoscopes are being developed worldwide [1][2][3][4][5][6].…”

Section: Introductionmentioning

confidence: 99%

A Subsample-Based Low-Power Image Compressor for Capsule Gastrointestinal Endoscopy

Lin

Dung

2011

EURASIP J. Adv. Signal Process.

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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.

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“…capsule endoscope endoscope using a communication link with magnetic induction. Our approach uses digital modulation with binary phase shift keying (BPSK) for video image transmission (10) . Communication is established by inductive coupling between the transmitter coil and the receiver coil using a modulated digital signal with 20MHz carrier.…”

Section: Introductionmentioning

confidence: 99%