Theses and Dissertations

Permanent URI for this collectionhttp://ir.daiict.ac.in/handle/123456789/1

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Subject: search.filters.subject.Wavelets

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    New learning based super resolution using contourlet transform
    (Dhirubhai Ambani Institute of Information and Communication Technology, 2009) Singh, Vineet P.; Joshi, Manjunath V.
    new learning based super-resolution reconstruction using contourlet transforms is proposed. contourlet transform provides high degree of directionality. It captures geometrical smoothness along multiple directions and learns the edges present in an image normal to the contour. For learning purpose, training set of low resolution (LR) and high resolution (HR) images, all captured using the same camera, are used. Here two and three level contourlet decomposition for LR images (test image and training image dataset) and HR training images respectively. The comparison of contourlet coeffcients of LR test image from the LR training set using minimum absolute difference (MAD) criterion to obtain the best match contourlet coeffcient. The finer details of test image are learned from the high resolution contourlet coefficients of the training data set. The inverse contourlet transform gives super resolved image corresponding to the test image.
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    Video compression using color transfer based on motion estimation
    (Dhirubhai Ambani Institute of Information and Communication Technology, 2008) Reddy, Pandu Ranga M.; Mitra, Suman K.
    Many compression techniques were developed in last decade and are being used in many applications like HDTV, Videoconferencing, Videophone, multimedia work stations and mobile image communications. It is also certain that digital video will have a significant economic impact on the computer, telecommunications, and imaging industries. Compression that is obtained by standard compression schemes for color video can be further increased if we can take the advantage of color information of successive images of a scene. The color of the objects in the present frame will be almost similar to the color of it in previous frame. So color can be applied at decoder, even if the information is not known for all frames of a scene. The main objective of this thesis is to propose schemes for different profiles of MPEG-2 which uses color transfer techniques. The proposed schemes are tested with different sequences and are compared with the MPEG-2 coded sequences.
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    FPGA implementation of image compression algorithm using wavelet transform
    (Dhirubhai Ambani Institute of Information and Communication Technology, 2008) Rawat, Nitin; Dubey, Rahul
    This work presents FPGA implementation of image compression algorithm by using wavelet transform. Here the emphasis has been made on algorithmic encoding, the first step of image compression problem. The transform that has been used for algorithmic encoding is the „Discrete Wavelet transform‟. The Wavelet family which has been used for this purpose is the „Haar Wavelet family. Various issues involved in hardware implementation of Wavelet Transform such as fractional interpretation, signed Q-format, range of gray scale values, memory requirement and addressing schemes have been discussed. A functional unit has been proposed which calculates the Wavelet transform of input pixel values. An efficient use of „Block RAM‟ present in FPGA has been proposed by placing the initial pixel values and then placing the computed Wavelet transform values back in this memory itself. A suitable way to tackle the issue of storing intermediate wavelet transform values by using a buffer memory has been suggested. This removes the need of having an external memory and thus the time required in accessing this memory reduces drastically. A special emphasis in order to use this memory in accordance with the requirement of image processing algorithms has been made by deriving the necessary addressing schemes. This is done in order to have the correct placement of transformed values in memory. Here we have used the Dual port feature of the Block RAM with one port providing multiple pixel values to the functional unit and other being used to write transformed values one at a time. Along with this, the DCM available in FPGA has been used to address issue of skew and „set up time‟ involved with the clocks in digital design. A delayed version of system clock is sent to memory so that all addresses and enable signals calculated with reference to system clock are stable when active edge of clock is received by memory. All these modules are incorporated in a top module which provides the Wavelet transform of an image. The modelling of the architecture has been done by using Verilog Hardware Description Language and the functional simulation has been done by using Xilinx ISE Simulator. The synthesis of the design has been done by using Xilinx Synthesis Tool (XST) of Xilinx. The total amount of the resources being utilized is reported and it comes out well within reach of Spartan 3E FPGA, our target device. The maximum clock frequency which can be used for the design comes out to be 23 MHz which is quite high for a compute intensive algorithm like Discrete Wavelet Transform.
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    On wavelets and fractal modulation
    (Dhirubhai Ambani Institute of Information and Communication Technology, 2004) Mehta, Shalin; Sinha, Virendra P.
    The thesis considers a communication problem - that of communicating over a channel having simultaneously unknown bandwidth and unknown duration. As a solution to this problem, the thesis looks into a modulation scheme - Fractal Modulation - proposed by Gregory Wornell and Alan Oppenheim. Wornell and Oppenheim have observed that requirements of reliable communication over such a channel can be met using ‘scale-diversity’ (transmitting the information at multiple time-scales). To achieve this scale-diversity, they have proposed the use of a particular class of self similar signals, called bihomogeneous signals. They have developed an inner product space representation of bihomogeneous signals. This representation stems from dyadic orhthonormal wavelet based expansion of bihomogeneous signals. Apart from providing very natural and convenient framework of signal representation, these wavelet based expansions lead to efficient algorithms for analysis and synthesis of these signals. This thesis critically analyzes links between important concepts of the general communication problem, the bihomogeneous signal model and wavelet based signal-processing methods. In the process, we have been able to achieve an understanding of the role of bihomogeneous signals and wavelet-based signal processing techniques in providing elegant and efficient solution to this unconventional problem. During the course of the thesis, we could implement and simulate the transmitter part of the complete communication system (transmitter, channel model and receiver). MATLAB was used for this purpose. The thesis presents implementation and simulation of algorithms for synthesizing channel waveform for Fractal Modulation scheme. The results of the simulation corroborate those expected from theoretical treatment.