Thesis (Ph. D.)--State University of New York at Binghamton, Thomas J. Watson School of Engineering and Applied Science, Department of Computer Science, 2008. / Includes bibliographical references.

Thesis (M.S.)--Rochester Institute of Technology, 2009. / Typescript. Includes bibliographical references (leaf 45).

Thesis (M.S.)--Rochester Institute of Technology, 2005. / Typescript. Includes bibliographical references (leaves 112-116).

Thesis (MEng)--Stellenbosch University, 2000. / ENGLISH ABSTRACT: The purpose of this thesis is to investigate the nature of digital image compression and the calculation of the quality of the compressed images. The work is focused on greyscale images in the domain of satellite images and aerial photographs. Two compression techniques are studied in detail namely the JPEG and fractal compression methods. Implementations of both these techniques are then applied to a set of test images. The rest of this thesis is dedicated to investigating the measurement of the loss of quality that was introduced by the compression. A general method for quality measurement (signal To Noise Ratio) is discussed as well as a technique that was presented in literature quite recently (Grey Block Distance). Hereafter, a new measure is presented. After this, a means of comparing the performance of these measures is presented. It was found that the new measure for image quality estimation performed marginally better than the SNR algorithm. Lastly, some possible improvements on this technique are mentioned and the validity of the method used for comparing the quality measures is discussed. / AFRIKAANSE OPSOMMING: Die doel van hierdie tesis is om ondersoek in te stel na die aard van digitale beeldsamepersing en die berekening van beeldkwaliteit na samepersing. Daar word gekonsentreer op grysvlak beelde in die spesifieke domein van satellietbeelde en lugfotos. Twee spesifieke samepersingstegnieke word in diepte ondersoek naamlik die JPEG en fraktale samepersingsmetodes. Implementasies van beide hierdie tegnieke word op 'n stel toetsbeelde aangewend. Die res van hierdie tesis word dan gewy aan die ondersoek van die meting van die kwaliteitsverlies van hierdie saamgeperste beelde. Daar word gekyk na 'n metode wat in algemene gebruik in die praktyk is asook na 'n nuwer metode wat onlangs in die literatuur veskyn het. Hierna word 'n nuwe tegniek bekendgestel. Verder word daar 'n vergelyking van hierdie mates en 'n ondersoek na die interpretasie van die 'kwaliteit' van hierdie kwaliteitsmate gedoen. Daar is gevind dat die nuwe maatstaf vir kwaliteit net so goed en selfs beter werk as die algemene maat vir beeldkwaliteit naamlik die Sein tot Ruis Verhouding. Laastens word daar moontlike verbeterings op die maatstaf genoem en daar volg 'n bespreking oor die geldigheid van die metode wat gevolg is om die kwaliteit van die kwaliteitsmate te bepaal

This thesis describes the design of fast JPEG processing accelerators for a DSP processor. Certain computation tasks are moved from the DSP processor to hardware accelerators. The accelerators are slave co processing machines and are controlled via a new instruction set. The clock cycle and power consumption is reduced by utilizing the custom built hardware. The hardware can perform the tasks in fewer clock cycles and several tasks can run in parallel. This will reduce the total number of clock cycles needed. First a decoder and an encoder were implemented in DSP assembler. The cycle consumption of the parts was measured and from this the hardware/software partitioning was done. Behavioral models of the accelerators were then written in C++ and the assembly code was modified to work with the new hardware. Finally, the accelerators were implemented using Verilog. Extension of the accelerator instructions was given following a custom design flow.

Due to limited hardware, effectively using the available resources is crucial for mobile games. Texture compression is a fundamental technique in game development to reduce the demand of memory and bandwidth usage. This thesis evaluates JPEG, PVRTC and uncompressed PVR with emphasis on loading time, memory footprint, application size and visual quality. The goal of this case study is to find the most suitable compression technique for a specific game. A variant of uncompressed PVR, RGBA4444, was found to be the best technique to use in this case. It was also concluded that JPEG compression in general is a bad choice for games due to the lack of an alpha channel. Severe visual artifacts were noticed on frame-by-frame animation when using PVRTC. It is therefore interesting to investigate other animation techniques, such as skeletal animation, in combination with texture compression, to avoid such artifacts.

Image sizes have increased exponentially in recent years. The resulting high-resolution images are often viewed via remote image browsing. Zooming and panning are desirable features in this context, which result in disparate spatial regions of an image being displayed at a variety of ( spatial) resolutions. When an image is displayed at a reduced resolution, the quantization step sizes needed for visually lossless quality generally increase. This paper investigates the quantization step sizes needed for visually lossless display as a function of resolution, and proposes a method that effectively incorporates the resulting ( multiple) quantization step sizes into a single JPEG 2000 codestream. This codestream is JPEG 2000 Part 1 compliant and allows for visually lossless decoding at all resolutions natively supported by the wavelet transform as well as arbitrary intermediate resolutions, using only a fraction of the full-resolution codestream. When images are browsed remotely using the JPEG 2000 Interactive Protocol ( JPIP), the required bandwidth is significantly reduced, as demonstrated by extensive experimental results.

This thesis deals with the management of digital photos by metadata contained in the photos. The thesis describes the structure of the formats JFIF, TIFF, RAW and EXIF format for storing metadata into photos. In the next part of this thesis is described the design and implementation of a simple photo management application. The main functionality of the application is focused on bulk editing EXIF metadata in the photos. In the conclusion of this thesis there's a proof of results and discussion about further extension options.

Background: With the boom in the internet space and social media platforms, a large number of images are being shared. With this rise and advancements in technology, many image editing tools have made their way to giving rise to digital image manipulation. Being able to differentiate a forged image is vital to avoid misinformation or misrepresentation. This study focuses on the splicing image forgery to localizes the forged region in the tampered image. Objectives: The main purpose of the thesis is to extend the capability of the JPEG Ghost model by localizing the tampering in the image. This is done by analyzing the difference curves formed by compressions in the tampered image, and thereafter comparing the performance of the models. Methods: The study is carried out by two research methods; one being a Literature Review, whose main goal is gaining insights on the existing studies in terms of the approaches and techniques followed; and the second being Experiment; whose main goal is to improve the JPEG ghost algorithm by localizing the forged area in a tampered image and to compare three machine learning models based on the performance metrics. The machine learning models that are compared are Random Forest, XGBoost, and Support Vector Machine. Results: The performance of the above-mentioned models has been compared with each other on the same dataset. Results from the experiment showed that XGBoost had the best overall performance over other models with the Jaccard Index value of 79.8%. Conclusions: The research revolves around localization of the forged region in a tampered image using the concept of JPEG ghosts. This is We have concluded that the performance of XGBoost model is the best, followed by Random Forest and then Support Vector Machine.

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