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Application of a logarithmic analog to digital converter to video processing
Title
Application of a logarithmic analog to digital converter to video processing.
Creator
Glatt, Terry Laurence., Florida Atlantic University, Glenn, William E.
Abstract/Description
Recent advances in integrated circuit technology have resulted in the manufacture of analog to digital converters with a logarithmic transfer characteristic that can operate at video rates. This thesis shows that applying this sort of non-linearity to video signals during digitizing will result in a system that will more closely match the human visual system. The appropriate background is presented including image reproduction, psychophysical aspects of perception, quantization error, and...
Show moreRecent advances in integrated circuit technology have resulted in the manufacture of analog to digital converters with a logarithmic transfer characteristic that can operate at video rates. This thesis shows that applying this sort of non-linearity to video signals during digitizing will result in a system that will more closely match the human visual system. The appropriate background is presented including image reproduction, psychophysical aspects of perception, quantization error, and contrast sensitivity. The background is then related to logarithmic processing with respect to minimizing contouring and improving the fidelity of detail in saturated colors. Finally, logarithmic processing was simulated using an image processor and prototype logarithmic analog to digital converters. The results of this demonstration are presented.
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Date Issued
1991
PURL
http://purl.flvc.org/fcla/dt/14691
Subject Headings
Analog-to-digital converters, Image transmission
Format
Document (PDF)
interlaced pixel delta codec: For transmission of video on low bit rate communication lines
Title
The interlaced pixel delta codec: For transmission of video on low bit rate communication lines.
Creator
Celi, Joseph, Jr., Florida Atlantic University, Furht, Borko, College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
Abstract/Description
The Interlaced Pixel Delta (IPD) Video Codec is a real time video compression and decompression engine. It is specifically designed to be used for video phone or video conferencing applications that are to be run under very low bandwidth networking conditions. The example network used throughout this dissertation is the Internet where users are typically connected at transmission speeds of 33.3 K bits per second or less. In order to accomplish this goal, the IPD codec must achieve very high...
Show moreThe Interlaced Pixel Delta (IPD) Video Codec is a real time video compression and decompression engine. It is specifically designed to be used for video phone or video conferencing applications that are to be run under very low bandwidth networking conditions. The example network used throughout this dissertation is the Internet where users are typically connected at transmission speeds of 33.3 K bits per second or less. In order to accomplish this goal, the IPD codec must achieve very high compression ratios. This feat is further complicated by the fact that the IPD codec is to be fully realized using a software approach in order to be considered a viable solution for the average Internet user. The demonstrated test results show that the IPD codec is capable of achieving these ambitious goals. The IPD compressor operates in a pipelined manner. Each stage in the IPD compression pipeline has its own complexities and challenges, which are individually addressed in detail. The ultimate goal of the IPD compressor is to maintain a constant compression ratio that is sufficiently high enough to allow bi-directional video communication to take place across low bandwidth transmission lines. These compression ratios must be achieved using a software compressor and decompressor. Strict CPU utilization requirements must be met by the IPD codec in order for it to be able to operate in real time. The IPD compressor defines a unique video interlacing scheme to sample the pixels that comprise the incoming video frames. The properties of the interlacing schemes aid the video compressor in its quest for high compression ratios. Later in the decompression stage, the IPD decompressor uses the properties of the interlacing schemes to reverse the sampling process to bring back the original picture quality. The IPD compressor also employs a custom variation of the error diffusion algorithm in its color reduction phase. A pixel delta algorithm is used to build a new frame from a previous frame. The pixel delta algorithm defines a unique bitmask representation of pixel locations that are flagged for refresh. These pixel locations will be used to build a subsequent frame. The bitmask representation of pixel locations is further compressed using a variation of the Huffman compression algorithm. An IPD delta frame is built by the IPD compressor. The IPD delta frame contains a header, the compressed bitmask of pixel locations flagged for change and the actual compressed pixel intensity values used used to build a new frame from a previous frame. The IPD decompressor also operates in a pipelined manner. The IPD decompressor also has strict requirements with respect to CPU utilization. The IPD decompressor applies several image processing algorithms to the video output stream in order to enhance the visual quality of the reconstructed output video frames. Custom test programs are used to derive and validate the algorithms presented in this dissertation. A working prototype of the complete IPD codec is also presented to aid in the visual analysis of the final video picture quality.
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Date Issued
1998
PURL
http://purl.flvc.org/fcla/dt/12573
Subject Headings
Internet videoconferencing, Video telephone, Image transmission
Format
Document (PDF)
Two-dimensional feature tracking algorithm for motion analysis
Title
Two-dimensional feature tracking algorithm for motion analysis.
Creator
Krishnan, Srivatsan., Florida Atlantic University, Raviv, Daniel, College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
Abstract/Description
In this thesis we describe a local-neighborhood-pixel-based adaptive algorithm to track image features, both spatially and temporally, over a sequence of monocular images. The algorithm assumes no a priori knowledge about the image features to be tracked, or the relative motion between the camera and the 3-D objects. The features to be tracked are selected by the algorithm and they correspond to the peaks of '2-D intensity correlation surface' constructed from a local neighborhood in the...
Show moreIn this thesis we describe a local-neighborhood-pixel-based adaptive algorithm to track image features, both spatially and temporally, over a sequence of monocular images. The algorithm assumes no a priori knowledge about the image features to be tracked, or the relative motion between the camera and the 3-D objects. The features to be tracked are selected by the algorithm and they correspond to the peaks of '2-D intensity correlation surface' constructed from a local neighborhood in the first image of the sequence to be analyzed. Any kind of motion, i.e., 6 DOF (translation and rotation), can be tolerated keeping in mind the pixels-per-frame motion limitations. No subpixel computations are necessary. Taking into account constraints of temporal continuity, the algorithm uses simple and efficient predictive tracking over multiple frames. Trajectories of features on multiple objects can also be computed. The algorithm accepts a slow, continuous change of brightness D.C. level in the pixels of the feature. Another important aspect of the algorithm is the use of an adaptive feature matching threshold that accounts for change in relative brightness of neighboring pixels. As applications of the feature-tracking algorithm and to test the accuracy of the tracking, we show how the algorithm has been used to extract the Focus of Expansion (FOE) and compute the Time-to-contact using real image sequences of unstructured, unknown environments. In both these applications, information from multiple frames is used.
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Date Issued
1994
PURL
http://purl.flvc.org/fcla/dt/15030
Subject Headings
Algorithms, Image transmission, Motion perception (Vision), Image processing
Format
Document (PDF)
Improving In Vivo Two Photon Microscopy Without Adaptive Optics
Title
Improving In Vivo Two Photon Microscopy Without Adaptive Optics.
Creator
Estrada, Gerardo, Beetle, Christopher, Florida Atlantic University, Charles E. Schmidt College of Science, Department of Physics
Abstract/Description
Two photon microscopy is one of the fastest growing methods of in-vivo imaging of the brain. It has the capability of imaging structures on the scale of 1μm. At this scale the wavelength of the imaging field (usually near infra-red), is comparable to the size of the structures being imaged, which makes the use of ray optics invalid. A better understanding is needed to predict the result of introducing different media into the light path. We use Wolf's integral, which is capable of fulfilling...
Show moreTwo photon microscopy is one of the fastest growing methods of in-vivo imaging of the brain. It has the capability of imaging structures on the scale of 1μm. At this scale the wavelength of the imaging field (usually near infra-red), is comparable to the size of the structures being imaged, which makes the use of ray optics invalid. A better understanding is needed to predict the result of introducing different media into the light path. We use Wolf's integral, which is capable of fulfilling these needs without the shortcomings of ray optics. We predict the effects of aberrating media introduced into the light path like glass cover-slips and then correct the aberration using the same method. We also create a method to predict aberrations when the interfaces of the media in the light-path are not aligned with the propagation direction of the wavefront.
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Date Issued
2015
PURL
http://purl.flvc.org/fau/fd/FA00004495
Subject Headings
Cellular signal transmission -- Measurement, Image analysis, Imaging systems in medicine, Membranes (Biology) -- Imaging, Neurons -- Imaging, Optics, Adaptive
Format
Document (PDF)
Structure and motion estimation from image sequences
Title
Structure and motion estimation from image sequences.
Creator
Shieh, Jen-yu., Florida Atlantic University, Zhuang, Hanqi, Sudhakar, Raghavan, College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
Abstract/Description
The objective of this dissertation is to develop effective algorithms for estimating the 3-D structure of a scene and its relative motion with respect to a camera or a pair of cameras from a sequence of images acquired by the cameras, under the assumption that the relative motion of the camera is small from one frame to another. This dissertation presents an approach of computing depth maps from an image sequence, which combines the direct depth estimation method with the optical flow based...
Show moreThe objective of this dissertation is to develop effective algorithms for estimating the 3-D structure of a scene and its relative motion with respect to a camera or a pair of cameras from a sequence of images acquired by the cameras, under the assumption that the relative motion of the camera is small from one frame to another. This dissertation presents an approach of computing depth maps from an image sequence, which combines the direct depth estimation method with the optical flow based method. More specifically, optical flow on and near moving edges are computed using a correlation technique. The optical flow information is then fused with the gradient information to estimate depth not only on moving edges but also in internal regions. Depth estimation is formulated as a discrete Kalman filter problem and is solved in three stages. In the prediction stage, the depth map estimated for the previous frame, together with knowledge of the camera motion, is used to predict the depth variance at each pixel in the current frame. In the estimation stage, a vector-version of Kalman filter formulation is adapted and simplified to refine the predicted depth map. The resulting estimation algorithm takes into account the information from the neighboring pixels, and thus is much more robust than the scalar-version Kalman filter implementation. In the smoothing stage, morphological filtering is applied to reduce the effect of measurement noise and fill in uncertain areas based on the error covariance information. Since the depth at each pixel is estimated locally, the algorithm presented in this paper can be implemented on a parallel computer. The performance of the presented method is assessed through simulation and experimental studies. A new approach for motion estimation from stereo image sequences is also proposed in this dissertation. First a stereo motion estimation model is derived using the direct dynamic motion estimation technique. The problem is then solved by applying a discrete Kalman filter that facilitates the use of a long stereo image sequence. Typically, major issues in such an estimation method are stereo matching, temporal matching, and noise sensitivity. In the proposed approach, owing to the use of temporal derivatives in the motion estimation model, temporal matching is not needed. The effort for stereo matching is kept to a minimum with a parallel binocular configuration. Noise smoothing is achieved by the use of a sufficiently large number of measurement points and a long sequence of stereo images. Both simulation and experimental studies have also been conducted to assess the effectiveness of the proposed approach.
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Date Issued
1992
PURL
http://purl.flvc.org/fcla/dt/12320
Subject Headings
Three-dimensional display systems, Imaging systems, Photography, Stereoscopic, Imaging transmission
Format
Document (PDF)
Interactive progressive encoding system for transmission of complex images
Title
Interactive progressive encoding system for transmission of complex images.
Creator
Furht, Borko, Wang, Yingli, Celli, Joseph
Date Issued
1998-11
PURL
http://purl.flvc.org/fcla/dt/351011
Subject Headings
Internetworking (Telecommunication), Digital video., Image transmission., JPEG (Image coding standard), Data compression (Telecommunication) --Standards., Image compression --Standards.
Format
Document (PDF)
Subband coding of images using binomial QMF and vector quantization
Title
Subband coding of images using binomial QMF and vector quantization.
Creator
Rajamani, Kannan., Florida Atlantic University, Erdol, Nurgun, College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
Abstract/Description
This thesis presents an image coding system using binomial QMF based subband decomposition and vector quantisation. An attempt was made to compress a still image of size 256 x 256 represented at a resolution of 8 bits/pixel to a bit rate of 0.5 bits/pixel using 16 channel subband decomposition with binomial QMFs and coding the subbands using a full search LBG Vector Quantizer (VQ). Simulations were done on SUN work station and the quality of the image was evaluated by computing the Signal to...
Show moreThis thesis presents an image coding system using binomial QMF based subband decomposition and vector quantisation. An attempt was made to compress a still image of size 256 x 256 represented at a resolution of 8 bits/pixel to a bit rate of 0.5 bits/pixel using 16 channel subband decomposition with binomial QMFs and coding the subbands using a full search LBG Vector Quantizer (VQ). Simulations were done on SUN work station and the quality of the image was evaluated by computing the Signal to Noise Ratio (SNR) between the original image and the reconstructed image.
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Date Issued
1995
PURL
http://purl.flvc.org/fcla/dt/15203
Subject Headings
Image compression--Digital techniques, Image processing--Digital techniques, Image transmission--Digital techniques, Coding theory, Vector fields
Format
Document (PDF)
Low complexity H.264 video encoder design using machine learning techniques
Title
Low complexity H.264 video encoder design using machine learning techniques.
Creator
Carrillo, Paula., Department of Computer and Electrical Engineering and Computer Science, College of Engineering and Computer Science
Abstract/Description
H.264/AVC encoder complexity is mainly due to variable size in Intra and Inter frames. This makes H.264/AVC very difficult to implement, especially for real time applications and mobile devices. The current technological challenge is to conserve the compression capacity and quality that H.264 offers but reduce the encoding time and, therefore, the processing complexity. This thesis applies machine learning technique for video encoding mode decisions and investigates ways to improve the...
Show moreH.264/AVC encoder complexity is mainly due to variable size in Intra and Inter frames. This makes H.264/AVC very difficult to implement, especially for real time applications and mobile devices. The current technological challenge is to conserve the compression capacity and quality that H.264 offers but reduce the encoding time and, therefore, the processing complexity. This thesis applies machine learning technique for video encoding mode decisions and investigates ways to improve the process of generating more general low complexity H.264/AVC video encoders. The proposed H.264 encoding method decreases the complexity in the mode decision inside the Inter frames. Results show, at least, a 150% average reduction of complexity and, at most, 0.6 average increases in PSNR for different kinds of videos and formats.
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Date Issued
2008
PURL
http://purl.flvc.org/FAU/166448
Subject Headings
Code division multiple access, Digital media, Technological innovations, Image transmission, Technological innovations, Coding theory, Data structures (Computer science)
Format
Document (PDF)
Video transcoding using machine learning
Title
Video transcoding using machine learning.
Creator
Holder, Christopher., College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
Abstract/Description
The field of Video Transcoding has been evolving throughout the past ten years. The need for transcoding of video files has greatly increased because of the new upcoming standards which are incompatible with old ones. This thesis takes the method of using machine learning for video transcoding mode decisions and discusses ways to improve the process of generating the algorithm for implementation in different video transcoders. The transcoding methods used decrease the complexity in the mode...
Show moreThe field of Video Transcoding has been evolving throughout the past ten years. The need for transcoding of video files has greatly increased because of the new upcoming standards which are incompatible with old ones. This thesis takes the method of using machine learning for video transcoding mode decisions and discusses ways to improve the process of generating the algorithm for implementation in different video transcoders. The transcoding methods used decrease the complexity in the mode decision inside the video encoder. Also methods which automate and improve results are discussed and implemented in two different sets of transcoders: H.263 to VP6 , and MPEG-2 to H.264. Both of these transcoders have shown a complexity loss of almost 50%. Video transcoding is important because the quantity of video standards have been increasing while devices usually can only decode one specific codec.
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Date Issued
2008
PURL
http://purl.flvc.org/FAU/166451
Subject Headings
Coding theory, Image transmission, Technological innovations, File conversion (Computer science), Data structures (Computer science), MPEG (Video coding standard), Digital media, Video compression
Format
Document (PDF)