MICROANGIOGRAM VIDEO COMPRESSION USING ADAPTIVE PREDICTION

Coronary angiography is an X-ray examination of the heart\u27s arteries. This is an essential technique for diagnosis of heart damages. Image sequences from digital angiography contain areas of high diagnostic interest. Loss of information due to compression for regions of interest (ROI) in angiograms is not tolerable. Since Commercially available technology such as JPEG and MPEG do not satisfy medical requirements due to their severe blockartifacts. In this paper, a new compression algorithm that achieves high compression ratio and excellent reconstruction quality for video rate or sub-video rate angiograms is developed. The proposed algorithm exploits temporal spatial and spectral redundancies in backward adaptive fashion with Extremely low side information. An experimental result shows that the proposed scheme provides significant improvements in compression efficiencies

Efficient Video Transport over Lossy Networks

Nowadays, packet video is an important application of the Internet. Unfortunately the capacity of the Internet is still very heterogeneous because it connects high bandwidth ATM networks as well as low bandwidth ISDN dial in lines. The MPEG-2 and MPEG-4 video compression standards provide efficient video encoding for high and low bandwidth media streams. In particular they include two paradigms which make those standards suitable for the transmission of video via heterogeneous networks. Both support layered video streams and MPEG-4 additionally allows the independent coding of video objects. In this paper we discuss those two paradigms, give an overview of the MPEG video compression standards and describe transport protocols for Real Time Media transport over lossy networks. Furthermore, we propose a real-time segmentation approach for extracting video objects in teleteaching scenarios

Computer Graphics and Visualization based Analysis and Record System for Hand Surgery and Therapy Practice

In this thesis, we have designed and developed a computer graphics and visualization based analysis and record system for hand surgery and therapy practice. In particular, we have designed and developed three novel technologies: (i) model-based data compression for hand motion records (ii) model-based surface area estimation of a human hand and (iii) an emulated study of hand wound area estimation. First, we have presented a new data compression technique to better address the needs of electronic health record systems, such as file storage and privacy. In our proposed approach, we will extract the patient\u27s hand motion information and store the motion data in a binary format, and then we use a loss less data compression to further reduce the file size. To illustrate this idea, we have built a prototype, which demonstrates our entire work flow. Our experiment results have shown the effective compression performance as well as added benefit of 3-D review, enhanced privacy and review capability at different playback speeds and view angles. Next, we developed a new approach, to estimate the surface area of a patient\u27s hand accurately and quickly with a low-cost imaging sensor and a graphics based hand model. Through the image capturing device, we capture infrared images of the patient\u27s hand. Once we get the input images, we run them through the image analysis engine to extract the required information in order to obtain a customized graphics hand object. Once customized we use the graphics hand object to calculate the surface area of the patient\u27s hand. To illustrate this idea, we have built a prototype system, which demonstrate the entire work flow. Our experiment results have shown considerable reproducibility and consistency. Finally, we came up with a novel system, capable of identifying simulated wounds on a human hand and estimating their area. Through the imaging device, wound analysis engines, we are able to identify simulated wounds on a patient\u27s hand and measure their area using optical equations. To illustrate this idea, we have built a prototype system, which demonstrates our entire work flow. Our experiments show considerable reproducibility, accuracy and consistency. In summary, we have developed prototypes for each of the approaches to demonstrate its capabilities. Experiments and analysis are carried out to study their performance and complexity. We believe these new approaches can significantly improve the current practice in hand surgery analysis and therapy practice

A Cost Shared Quantization Algorithm and its Implementation for Multi-Standard Video CODECS

The current trend of digital convergence creates the need for the video encoder and decoder system, known as codec in short, that should support multiple video standards on a single platform. In a modern video codec, quantization is a key unit used for video compression. In this thesis, a generalized quantization algorithm and hardware implementation is presented to compute quantized coefficient for six different video codecs including the new developing codec High Efficiency Video Coding (HEVC). HEVC, successor to H.264/MPEG-4 AVC, aims to substantially improve coding efficiency compared to AVC High Profile. The thesis presents a high performance circuit shared architecture that can perform the quantization operation for HEVC, H.264/AVC, AVS, VC-1, MPEG- 2/4 and Motion JPEG (MJPEG). Since HEVC is still in drafting stage, the architecture was designed in such a way that any final changes can be accommodated into the design. The proposed quantizer architecture is completely division free as the division operation is replaced by multiplication, shift and addition operations. The design was implemented on FPGA and later synthesized in CMOS 0.18 μm technology. The results show that the proposed design satisfies the requirement of all codecs with a maximum decoding capability of 60 fps at 187.3 MHz for Xilinx Virtex4 LX60 FPGA of a 1080p HD video. The scheme is also suitable for low-cost implementation in modern multi-codec systems