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Image compression with DCT, quantization encoding method transform coding is widely used in image processing technique, however in these transformations the 2-D images are divided into sub-blocks and each block is transformed separately and into elementary frequency components. There frequency components (DC & AC) are reducing to zero during the process of quantization which is a lossy process. In this paper we are discussing about the image compression techniques with DCT and quantization method for reducing the blocking artifacts in reconstruction. The proposed method applies to several images and its performance is further analyzed for the reduction in image size. The picture quality between the original image and reconstructed image measured with PSNR value with different quantization matrices.

Increase in multimedia applications drastically increased the demand for digital information. Reduction in the size of this data for transmission and storage is very important. This is done by Image compression. JPEG (Joint Photographic Experts Group) is an international compression standard for continuous-tone still image, both grayscale and color. There are software solutions as well as hardware solutions for JPEG compression depending upon the application. Hardware solutions are mainly used for high speed and parallel processing applications. As the distinct requirement for each of the applications, the JPEG standard has two basic compression methods. The DCT-based method is specified for lossy compression, and the predictive method is specified for lossless compression. Simple lossy technique is baseline, which is a DCT-based method, has been widely used and is sufficient for a large number of applications. In this paper, introduce the JPEG standard and focuses on the baseline method. The objective is to implement hardware based Discrete Cosine Transform (DCT/IDCT) Processor and Controller for high throughput Image compression. Images have certain statistical properties which can be exploited by specifically designed encoders. Some of the finer details in the image can be sacrificed for less storage space. Images need not be reproduced 'exactly'. An approximation of the original image is enough for most purposes, as long as the error between the original and the compressed image is tolerable. The main aim of this project is to develop a method for JPEG encoding to process large images of size 10M pixel or more. Encoding such a large size images in short duration is difficult in traditional software or hardware methods. This paper involves development of JPEG encoder with parallel processing techniques to compress 10M pixels or more in size images in 40 milliseconds time frame. Project implementation involves development of digital blocks, coding of logic in VHDL, Verification of functionality with Verilog HDL test-bench, synthesis of logic in Altera Cyclone-III FPGA and demonstrate the functionality.

Image compression is a very essential process in this multimedia computer era, it keeps the file size of the digital image as low as possible either for hardware storage requirements or for fast transmission times. Many graphic compression schemes have been developed over the last decade. This paper mainly concentrates on " Recursive Least Squares Dictionary Learning Algorithm " RLS-DLA, which can be used for learning over-complete dictionaries for sparse signal representation. The training set is used continuously to update the dictionary recursively as each training vector is being processed. We implemented RLS-DLA approach by scheme of convergence considering forgetting factor λ, the core of the algorithm is compact and can be effectively implemented. Moreover, we worked on comparative analysis of RLS-DLA with older natural image compression techniques like JPEG, JPEG2000. Finally, the low bit rate image compression can be achieved, owing the sparsity coefficients by RLS-DLA approach. The experimental results demonstrate the effectiveness of RLS-DLA approach on compressing the natural images at low bit rates.

Tech Talk July 29

Data compression is the reduction or elimination of redundancy in data representation in order to achieve savings in storage and communication costs. Data compression techniques can be broadly classified into two categories: Lossless, Lossy schemes. Digital images require an enormous amount of space for storage. The architecture exploits the principles of pipelining and parallelism to the maximum extent in order to obtain high speed the architecture for discrete cosine transforms and the entropy encoder are based on efficient algorithms designed for high speed VLSI. For example, a colour image with a resolution of 1024 x 1024 picture elements (pixels) with 24 bits per pixel would require 3.15 Mbytes in uncompressed form. Very high-speed design of efficient compression techniques will significantly help in meeting that challenge. The JPEG baseline algorithm consists mainly of two parts: (i) Discrete Cosine Transform (DCT) computation and (ii) Entropy encoding. The architecture for entropy encoding is based on a hardware algorithm designed to yield maximum clock speed

Objectives: This paper intends to propose a secure steganography approach in JPEG compressed domain by providing more possibilities to analyzing the DCT coefficients in lower frequency area by modifying the primary Quantization Table (QT) with generating random data hiding patterns. Methods/Statistical analysis: The upper left part of the primary QT extracted from gray scale image dataset is modified by multiplying the factors ¼, ½ and ¾ to produce secondary QTs for investigating randomly generated data hiding patterns in lower frequency area of quantized DCT coefficients by Least Significant Bit (LSB) method. We create a pool of QTs and those tables are cross checked with randomly generated hiding patterns to find best QT with appropriate data hiding pattern by assessing Peak Signal to Noise Ratio (PSNR). Our method can be used to attain trade-off between some parameters such as image features, QT, data hiding pattern. Further, statistical features of a given image data set are extracted and analyzed with the selected QT and appropriate hiding pattern by using R software. Findings: The Experimental results revealed that our proposed method can embed high capacity data (57 bits per block) without noticeable visual artifacts by considering lower frequency coefficients for data hiding by assessing the image steganographic requirements. The maximum PSNR value 48 and the minimum PSNR value 32 are found among the fifty jpeg gray images based on their contents. Although, the embedding capacity and PSNR fluctuate among images, our method can be used to attain trade-off between some parameters such as image features, QT, data hiding pattern. Further, statistical features of a given image data set are extracted and analyzed with the selected QT and appropriate hiding pattern using R. The hypothesis test was deployed among the QTs, hiding patterns and image features. The following five P-Values, 0.04128, 0.02486, 0.02241, 0.04898, 0.01966 less than 0.05 show the good relationship between the QTs, hiding patterns and image features among the cover images and also the following four P-Values, 0.00685, 0.03017, 0.001085, 4.568e-12, less than 0.05, show the good relationship between those above mentioned factors among the stego images. Application/Improvements: Finally, we present a secure model to explore the relationship between QT, hiding pattern and image contents. The found model is stego invariant for sender and receiver that will enable them to identify QT and pattern by extracting the image features without fully decoding the stego jpeg image. This method is very practical and adaptable for extending QTs and hiding patterns.

Purpose: Behçet's uveitis is not common in western Europe and thedisease presentation is less obvious than in ``endemic'' countries such as Turkeyand Japan. This makes the diagnosis more difficult. Early diagnosis is important, as the prognosis is better if therapy is started early. New methods such as ultrasoundbiomicroscopy (UBM) and indocyanine green angiography (ICGA) can improve thecharacterisation and diagnosis of uveitis. Our purpose was to present our experiencewith these new methods as well as HLA-B51 testing in the appraisal of patients withBehçet's uveitis.Patients and Methods: Patients seen by the authors between 1997 and 2001with Behçet's uveitis or suspected Behçet's uveitis and who underwentICG angiography or UBM were included. Symptoms and signs, results of laboratorywork-up including HLA-B51 antigen testing and the delay to diagnosis, were analysed.Fluorescein and ICG angiography and UBM testing were performed according tostandard protocols used for uveitis patients and their contribution towards diagnosisand management were analysed.Results: Uveitis was non granulomatous in all patients. Fluorescein angiography showed moderate to severe diffuse retinal vasculitis compatiblewith Behçet's uveitis in all cases. HLA-B51 testing was positive in 5 of 7tested cases, being useful to orient the diagnosis. UBM contributed to thediagnosis in all five tested cases, being the determining element in 3 patients.It allowed redirection of the diagnosis from pars planitis to Behçet's in 2patients with poorly transparent media because it failed to show the typicalpars planitis deposits. In a case originally diagnosed as Behçet's it allowedcorrection of the diagnosis to pars planitis because of the presence of the typicalUBM pars plana depositis. ICG angiography allowed detection of choroidalvasculitis in all five tested cases.Conclusions: In Behçet's patients who did not present with a full-blownclinical picture, as they are often seen in non-endemic areas, UBM examinationand HLA-B51 testing were valuable additional diagnostic elements helping toredirect the diagnosis correctly and to reduce the diagnostic delay in these patients.The hitherto unknown choroidal vasculitis shown by ICG angiography in all fiveinvestigated patients indicates that choroidal involvement probably occurs in mostnewly diagnosed Behçet's patients.When we first reviewed JPEGmini,

Automatically Compress Images Without Losing Quality

Data compression is the reduction or elimination of redundancy in data representation in order to achieve savings in storage and communication costs. Data compression techniques can be broadly classified into two categories: Lossless, Lossy schemes. Digital images require an enormous amount of space for storage. The architecture exploits the principles of pipelining and parallelism to the maximum extent in order to obtain high speed the architecture for discrete cosine transforms and the entropy encoder are based on efficient algorithms designed for high speed VLSI. For example, a colour image with a resolution of 1024 x 1024 picture elements (pixels) with 24 bits per pixel would require 3.15 Mbytes in uncompressed form. Very high-speed design of efficient compression techniques will significantly help in meeting that challenge. The JPEG baseline algorithm consists mainly of two parts: (i) Discrete Cosine Transform (DCT) computation and (ii) Entropy encoding. The architecture for entropy encoding is based on a hardware algorithm designed to yield maximum clock speed

Objectives: This paper intends to propose a secure steganography approach in JPEG compressed domain by providing more possibilities to analyzing the DCT coefficients in lower frequency area by modifying the primary Quantization Table (QT) with generating random data hiding patterns. Methods/Statistical analysis: The upper left part of the primary QT extracted from gray scale image dataset is modified by multiplying the factors ¼, ½ and ¾ to produce secondary QTs for investigating randomly generated data hiding patterns in lower frequency area of quantized DCT coefficients by Least Significant Bit (LSB) method. We create a pool of QTs and those tables are cross checked with randomly generated hiding patterns to find best QT with appropriate data hiding pattern by assessing Peak Signal to Noise Ratio (PSNR). Our method can be used to attain trade-off between some parameters such as image features, QT, data hiding pattern. Further, statistical features of a given image data set are extracted and analyzed with the selected QT and appropriate hiding pattern by using R software. Findings: The Experimental results revealed that our proposed method can embed high capacity data (57 bits per block) without noticeable visual artifacts by considering lower frequency coefficients for data hiding by assessing the image steganographic requirements. The maximum PSNR value 48 and the minimum PSNR value 32 are found among the fifty jpeg gray images based on their contents. Although, the embedding capacity and PSNR fluctuate among images, our method can be used to attain trade-off between some parameters such as image features, QT, data hiding pattern. Further, statistical features of a given image data set are extracted and analyzed with the selected QT and appropriate hiding pattern using R. The hypothesis test was deployed among the QTs, hiding patterns and image features. The following five P-Values, 0.04128, 0.02486, 0.02241, 0.04898, 0.01966 less than 0.05 show the good relationship between the QTs, hiding patterns and image features among the cover images and also the following four P-Values, 0.00685, 0.03017, 0.001085, 4.568e-12, less than 0.05, show the good relationship between those above mentioned factors among the stego images. Application/Improvements: Finally, we present a secure model to explore the relationship between QT, hiding pattern and image contents. The found model is stego invariant for sender and receiver that will enable them to identify QT and pattern by extracting the image features without fully decoding the stego jpeg image. This method is very practical and adaptable for extending QTs and hiding patterns.

Purpose: Behçet's uveitis is not common in western Europe and thedisease presentation is less obvious than in ``endemic'' countries such as Turkeyand Japan. This makes the diagnosis more difficult. Early diagnosis is important, as the prognosis is better if therapy is started early. New methods such as ultrasoundbiomicroscopy (UBM) and indocyanine green angiography (ICGA) can improve thecharacterisation and diagnosis of uveitis. Our purpose was to present our experiencewith these new methods as well as HLA-B51 testing in the appraisal of patients withBehçet's uveitis.Patients and Methods: Patients seen by the authors between 1997 and 2001with Behçet's uveitis or suspected Behçet's uveitis and who underwentICG angiography or UBM were included. Symptoms and signs, results of laboratorywork-up including HLA-B51 antigen testing and the delay to diagnosis, were analysed.Fluorescein and ICG angiography and UBM testing were performed according tostandard protocols used for uveitis patients and their contribution towards diagnosisand management were analysed.Results: Uveitis was non granulomatous in all patients. Fluorescein angiography showed moderate to severe diffuse retinal vasculitis compatiblewith Behçet's uveitis in all cases. HLA-B51 testing was positive in 5 of 7tested cases, being useful to orient the diagnosis. UBM contributed to thediagnosis in all five tested cases, being the determining element in 3 patients.It allowed redirection of the diagnosis from pars planitis to Behçet's in 2patients with poorly transparent media because it failed to show the typicalpars planitis deposits. In a case originally diagnosed as Behçet's it allowedcorrection of the diagnosis to pars planitis because of the presence of the typicalUBM pars plana depositis. ICG angiography allowed detection of choroidalvasculitis in all five tested cases.Conclusions: In Behçet's patients who did not present with a full-blownclinical picture, as they are often seen in non-endemic areas, UBM examinationand HLA-B51 testing were valuable additional diagnostic elements helping toredirect the diagnosis correctly and to reduce the diagnostic delay in these patients.The hitherto unknown choroidal vasculitis shown by ICG angiography in all fiveinvestigated patients indicates that choroidal involvement probably occurs in mostnewly diagnosed Behçet's patients.When we first reviewed JPEGmini,

Automatically Compress Images Without Losing Quality

Data compression is the reduction or elimination of redundancy in data representation in order to achieve savings in storage and communication costs. Data compression techniques can be broadly classified into two categories: Lossless, Lossy schemes. Digital images require an enormous amount of space for storage. The architecture exploits the principles of pipelining and parallelism to the maximum extent in order to obtain high speed the architecture for discrete cosine transforms and the entropy encoder are based on efficient algorithms designed for high speed VLSI. For example, a colour image with a resolution of 1024 x 1024 picture elements (pixels) with 24 bits per pixel would require 3.15 Mbytes in uncompressed form. Very high-speed design of efficient compression techniques will significantly help in meeting that challenge. The JPEG baseline algorithm consists mainly of two parts: (i) Discrete Cosine Transform (DCT) computation and (ii) Entropy encoding. The architecture for entropy encoding is based on a hardware algorithm designed to yield maximum clock speed

Objectives: This paper intends to propose a secure steganography approach in JPEG compressed domain by providing more possibilities to analyzing the DCT coefficients in lower frequency area by modifying the primary Quantization Table (QT) with generating random data hiding patterns. Methods/Statistical analysis: The upper left part of the primary QT extracted from gray scale image dataset is modified by multiplying the factors ¼, ½ and ¾ to produce secondary QTs for investigating randomly generated data hiding patterns in lower frequency area of quantized DCT coefficients by Least Significant Bit (LSB) method. We create a pool of QTs and those tables are cross checked with randomly generated hiding patterns to find best QT with appropriate data hiding pattern by assessing Peak Signal to Noise Ratio (PSNR). Our method can be used to attain trade-off between some parameters such as image features, QT, data hiding pattern. Further, statistical features of a given image data set are extracted and analyzed with the selected QT and appropriate hiding pattern by using R software. Findings: The Experimental results revealed that our proposed method can embed high capacity data (57 bits per block) without noticeable visual artifacts by considering lower frequency coefficients for data hiding by assessing the image steganographic requirements. The maximum PSNR value 48 and the minimum PSNR value 32 are found among the fifty jpeg gray images based on their contents. Although, the embedding capacity and PSNR fluctuate among images, our method can be used to attain trade-off between some parameters such as image features, QT, data hiding pattern. Further, statistical features of a given image data set are extracted and analyzed with the selected QT and appropriate hiding pattern using R. The hypothesis test was deployed among the QTs, hiding patterns and image features. The following five P-Values, 0.04128, 0.02486, 0.02241, 0.04898, 0.01966 less than 0.05 show the good relationship between the QTs, hiding patterns and image features among the cover images and also the following four P-Values, 0.00685, 0.03017, 0.001085, 4.568e-12, less than 0.05, show the good relationship between those above mentioned factors among the stego images. Application/Improvements: Finally, we present a secure model to explore the relationship between QT, hiding pattern and image contents. The found model is stego invariant for sender and receiver that will enable them to identify QT and pattern by extracting the image features without fully decoding the stego jpeg image. This method is very practical and adaptable for extending QTs and hiding patterns.

Purpose: Behçet's uveitis is not common in western Europe and thedisease presentation is less obvious than in ``endemic'' countries such as Turkeyand Japan. This makes the diagnosis more difficult. Early diagnosis is important, as the prognosis is better if therapy is started early. New methods such as ultrasoundbiomicroscopy (UBM) and indocyanine green angiography (ICGA) can improve thecharacterisation and diagnosis of uveitis. Our purpose was to present our experiencewith these new methods as well as HLA-B51 testing in the appraisal of patients withBehçet's uveitis.Patients and Methods: Patients seen by the authors between 1997 and 2001with Behçet's uveitis or suspected Behçet's uveitis and who underwentICG angiography or UBM were included. Symptoms and signs, results of laboratorywork-up including HLA-B51 antigen testing and the delay to diagnosis, were analysed.Fluorescein and ICG angiography and UBM testing were performed according tostandard protocols used for uveitis patients and their contribution towards diagnosisand management were analysed.Results: Uveitis was non granulomatous in all patients. Fluorescein angiography showed moderate to severe diffuse retinal vasculitis compatiblewith Behçet's uveitis in all cases. HLA-B51 testing was positive in 5 of 7tested cases, being useful to orient the diagnosis. UBM contributed to thediagnosis in all five tested cases, being the determining element in 3 patients.It allowed redirection of the diagnosis from pars planitis to Behçet's in 2patients with poorly transparent media because it failed to show the typicalpars planitis deposits. In a case originally diagnosed as Behçet's it allowedcorrection of the diagnosis to pars planitis because of the presence of the typicalUBM pars plana depositis. ICG angiography allowed detection of choroidalvasculitis in all five tested cases.Conclusions: In Behçet's patients who did not present with a full-blownclinical picture, as they are often seen in non-endemic areas, UBM examinationand HLA-B51 testing were valuable additional diagnostic elements helping toredirect the diagnosis correctly and to reduce the diagnostic delay in these patients.The hitherto unknown choroidal vasculitis shown by ICG angiography in all fiveinvestigated patients indicates that choroidal involvement probably occurs in mostnewly diagnosed Behçet's patients.When we first reviewed JPEGmini,

Automatically Compress Images Without Losing Quality

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