Full image-processing pipeline in field-programmable gate array for a small endoscopic camera

Endoscopy is an imaging procedure used for diagnosis as well as for some surgical purposes. The camera used for the endoscopy should be small and able to produce a good quality image or video, to reduce discomfort of the patients, and to increase the efficiency of the medical team. To achieve these fundamental goals, a small endoscopy camera with a footprint of 1 mm × 1 mm × 1.65 mm is used. Due to the physical prop erties of the sensors and human vision system limitations, different image-processing algorithms, such as noise reduction, demosaicking, and gamma correction, among others, are needed to faithfully reproduce the image or video. A full image-processing pipeline is implemented using a field-programmable gate array (FPGA) to accomplish a high frame rate of 60 fps with minimum processing delay. Along with this, a viewer has also been developed to display and control the image-processing pipeline. The control and data transfer are done by a USB 3.0 end point in the computer. The full developed system achieves real-time processing of the image and fits in a Xilinx Spartan-6LX150 FPGA.info:eu-repo/semantics/publishedVersio

Programmable Spectral Source and Design Tool for 3D Imaging Using Complementary Bandpass Filters

An endoscopic illumination system for illuminating a subject for stereoscopic image capture, includes a light source which outputs light; a first complementary multiband bandpass filter (CMBF) and a second CMBF, the first and second CMBFs being situated in first and second light paths, respectively, where the first CMBF and the second CMBF filter the light incident thereupon to output filtered light; and a camera which captures video images of the subject and generates corresponding video information, the camera receiving light reflected from the subject and passing through a pupil CMBF pair and a detection lens. The pupil CMBF includes a first pupil CMBF and a second pupil CMBF, the first pupil CMBF being identical to the first CMBF and the second pupil CMBF being identical to the second CMBF, and the detection lens includes one unpartitioned section that covers both the first pupil CMBF and the second pupil CMBF

An FPGA-based versatile development system for endoscopic capsule design optimization

This work presents a development system, based on Field Programmable Gate Array (FPGA), that was specifically designed for testing the entire electronics to be integrated in an endoscopic capsule, such as a camera, an image compression engine, a high-speed telemetric system, illumination and inertial sensors. Thanks to its high flexibility, several features were tested and evaluated, thus allowing to find the optimal configuration, in terms of power consumption, performances and size, to be fit in a capsule. As final result, an average frame rate of 19 frame per second (fps) over a transmission channel of 1.5 Mbit/s was chosen as the best choice for the development of a miniaturized endoscopic capsule prototype

A full-custom digital-signal-processing unit for real-time cortical blood flow monitoring

Master'sMASTER OF ENGINEERIN

A 72 × 60 Angle-Sensitive SPAD Imaging Array for Lens-less FLIM

We present a 72 × 60, angle-sensitive single photon avalanche diode (A-SPAD) array for lens-less 3D fluorescence lifetime imaging. An A-SPAD pixel consists of (1) a SPAD to provide precise photon arrival time where a time-resolved operation is utilized to avoid stimulus-induced saturation, and (2) integrated diffraction gratings on top of the SPAD to extract incident angles of the incoming light. The combination enables mapping of fluorescent sources with different lifetimes in 3D space down to micrometer scale. Futhermore, the chip presented herein integrates pixel-level counters to reduce output data-rate and to enable a precise timing control. The array is implemented in standard 180 nm complementary metal-oxide-semiconductor (CMOS) technology and characterized without any post-processing

Neuromorphic electronics for real-time biomedical image processing

Published versio

A low complexity image compression algorithm for Bayer color filter array

Digital image in their raw form requires an excessive amount of storage capacity. Image compression is a process of reducing the cost of storage and transmission of image data. The compression algorithm reduces the file size so that it requires less storage or transmission bandwidth. This work presents a new color transformation and compression algorithm for the Bayer color filter array (CFA) images. In a full color image, each pixel contains R, G, and B components. A CFA image contains single channel information in each pixel position, demosaicking is required to construct a full color image. For each pixel, demosaicking constructs the missing two-color information by using information from neighbouring pixels. After demosaicking, each pixel contains R, G, and B information, and a full color image is constructed. Conventional CFA compression occurs after the demosaicking. However, the Bayer CFA image can be compressed before demosaicking which is called compression-first method, and the algorithm proposed in this research follows the compression-first or direct compression method. The compression-first method applies the compression algorithm directly onto the CFA data and shifts demosaicking to the other end of the transmission and storage process. The advantage of the compression-first method is that it requires three time less transmission bandwidth for each pixel than conventional compression. Compression-first method of CFA data produces spatial redundancy, artifacts, and false high frequencies. The process requires a color transformation with less correlation among the color components than that Bayer RGB color space. This work analyzes correlation coefficient, standard deviation, entropy, and intensity range of the Bayer RGB color components. The analysis provides two efficient color transformations in terms of features of color transformation. The proposed color components show lesser correlation coefficient than occurs with the Bayer RGB color components. Color transformations reduce both the spatial and spectral redundancies of the Bayer CFA image. After color transformation, the components are independently encoded using differential pulse-code modulation (DPCM) in raster order fashion. The residue error of DPCM is mapped to a positive integer for the adaptive Golomb rice code. The compression algorithm includes both the adaptive Golomb rice and Unary coding to generate bit stream. Extensive simulation analysis is performed on both simulated CFA and real CFA datasets. This analysis is extended for the WCE (wireless capsule endoscopic) images. The compression algorithm is also realized with a simulated WCE CFA dataset. The results show that the proposed algorithm requires less bits per pixel than the conventional CFA compression. The algorithm also outperforms recent works on CFA compression algorithms for both real and simulated CFA datasets

書き換え可能なゲートアレイを用いた無作為抽出法に基づく実時間画像処理に関する研究

長崎大学学位論文 学位記番号:博(工)甲第53号 学位授与年月日:平成30年3月20日Nagasaki University (長崎大学)課程博