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Remote visualization of volumetric data has gained importance over the past few years in order to realize the full potential of tele-radiology. Volume rendering is a computationally intensive process, often requiring hardware acceleration to achieve real time visualization. Hence a remote visualization model that is well-suited for high speed netwo...
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... paper is organized as follows. Section 2 describes the remote visualization model. In Section 3, we present our Scalable Low Complexity Coder (SLCC). In Section 4, we present compression and throughput performance. Fig. 1 shows the client-server communication system. All the steps in the volume rendering pipeline are executed at the server using dedicated hardware. Based on view point requests from a client, the server transmits the sequence of 2D rendered images interactively. With unconstrained bandwidth, raw images can be sent to get lossless real ...
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... the use of a decorrelating transform. The YCbCr transform that is generally used for natural RGB images did not yield any improvement for our test images. Experimental results are presented with 2 test sequences. These 2 sequences were obtained using different rendering parameters. Each sequence has 30 frames and the frame size is 600×600. Fig. 10(a) shows the 1 st frame in test sequence 1. The throughput performance of SLCC is compared with kakadu V5.0 -an efficient JPEG2000 software 13 implementation (see footnote on pg 2). Timing experiments were carried out on a PC with 'Intel Core2 Duo T5470 1.6GHz' processor and 2GB ...
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... Thus the image quality with kakadu V5.0 will be limited to 33.03 dB (PSNR at 0.76 bpp) at all bandwidths greater than 7.8 Mbps. If the available bandwidth exceeds approximately 15 Mbps, SLCC can use the available data to yield higher PSNR than kakadu V5.0. For faster JPEG2000 implementations, this crossover will occur at higher bandwidths. Fig. 10b and Fig. 10c show the decompressed images from kakadu V5.0 and SLCC respectively, when the availble bandwidth is 70 Mbps. As seen from the figure, SLCC can display very high quality images at this bandwidth. ...
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... image quality with kakadu V5.0 will be limited to 33.03 dB (PSNR at 0.76 bpp) at all bandwidths greater than 7.8 Mbps. If the available bandwidth exceeds approximately 15 Mbps, SLCC can use the available data to yield higher PSNR than kakadu V5.0. For faster JPEG2000 implementations, this crossover will occur at higher bandwidths. Fig. 10b and Fig. 10c show the decompressed images from kakadu V5.0 and SLCC respectively, when the availble bandwidth is 70 Mbps. As seen from the figure, SLCC can display very high quality images at this bandwidth. ...
Citations
Remote visualization of volumetric images has gained importance over the past few years in medical and industrial applications. Volume visualization is a computationally intensive process, often requiring hardware acceleration to achieve a real time viewing experience. One remote visualization model that can accomplish this would transmit rendered images from a server, based on viewpoint requests from a client. For constrained server-client bandwidth, an efficient compression scheme is vital for transmitting high quality rendered images. In this paper, we present a new view compensation scheme that utilizes the geometric relationship between viewpoints to exploit the correlation between successive rendered images. The proposed method obviates motion estimation between rendered images, enabling significant reduction to the complexity of a compressor. Additionally, the view compensation scheme, in conjunction with JPEG2000 performs better than AVC, the state of the art video compression standard.
Remote visualization of volumetric images has gained importance over the past few years in medical and industrial applications. Volume visualization is a computationally intensive process, often requiring hardware acceleration to achieve a real time viewing experience. One remote visualization model that can accomplish this would transmit rendered images (with dedicated hardware) from the server based on view-point requests from a client. For a given server-client bandwidth, an efficient compression scheme is vital for transmitting high quality rendered images. In this paper, we present a new compression scheme that utilizes the geometric relationship between view-points to exploit the correlation between successive rendered images. The proposed method performs better than AVC, the state of the art video compression standard. Additionally, our scheme obviates motion estimation between rendered images, enabling significant reduction to the complexity of the encoder.
