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Comparative Performance Analysis of Haar, Symlets and Bior wavelets on Image compression using Discrete Wavelet Transform
Jashanbir Singh Kaleka
International Journal of Computer and Distributed System , 2012,
Abstract: This paper aims at performing wavelet analysis on jpeg images using discrete wavelet transform for implementation in a still image compression system and to highlight the benefit of this transform relating to other techniques (DCT). The paper discusses important features of wavelet transform in compression of still images, including the extent to which the quality of image is degraded by the process of wavelet compression and decompression and checks the results in terms of image quality metrics PSNR and also computes compression ratios at different level of decompositions of DWT. Haar, Symlets and Biorthogonal wavelets have been applied to an image and results have been compared in the form of qualitative and quantitative analysis in terms of PSNR values and compression ratios. Elapsed times for compression of image for different wavelets have also been computed to get the fast image compression method. Algorithm follows a quantization approach that divides the input image in 4 filter coefficients and then performs further quantization on the lower order filter or window of the previous step that has been developed using MATLAB software. Image quality is measured objectively, using peak signal-to-noise ratio or picture quality scale, and subjectively, using perceived image quality. These results provide a good reference for application developers to choose a good wavelet compression system for their application.
Time Domain Signal Analysis Using Modified Haar and Modified Daubechies Wavelet Transform  [cached]
Daljeet Kaur Khanduja,M.Y.Gokhale
Signal Processing : An International Journal , 2010,
Abstract: In this paper, time signal analysis and synthesis based on modified Haar and modified Daubechies wavelet transform is proposed. The optimal results for both analysis and synthesis for time domain signals were obtained with the use of the modified Haar and modified Daubechies wavelet transforms. This paper evaluates the quality of filtering using the modified Haar and modified Daubechies wavelet transform. Analysis and synthesis of the time signals is performed for 10 samples and the signal to noise ratio (SNR) of around 25-40 dB is obtained for modified Haar and 24-32 dB for modified Daubechies wavelet. We have observed that as compared to standard Haar and standard Daubechies mother wavelet our proposed method gives better signal quality, which is good for time varying signals.
An Efficient Method of Watermarking Using Multi Wavelet Technique with Modified Fast Haar Wavelet Transform (MFHWT)  [PDF]
Shefaly Sharma,Jagpreet Kaur
International Journal of Innovative Technology and Exploring Engineering , 2013,
Abstract: Now a day we share huge amount of data through internet. Data can be of the form of text, image audio or video. We also share critical information with others. Major issue now a days is to secure our data from third person so that it can be protected from harm. In that case third person can make misuse of our data. So, to solve this problem we will make use of a new technique called Watermarking using Modified Fast Haar Wavelet Transform (MFHWT). Watermarking is a technique used for hiding the data. We need to hide the information such that any change in the data should be imperceptible. It also helps us in know whether the data is having copyright or not.
Localization of Text in Complex Images Using Haar Wavelet Transform  [PDF]
Neha Gupta,,Dr. V.K.Banga
International Journal of Innovative Technology and Exploring Engineering , 2012,
Abstract: In this paper, a new hybrid approach is developed which locate text in different backgrounds. However, variation of text due to differences in size, style, orientation and alignment, as well as low image contrast and complex background make the problem of automatic text localization extremely challenging. The text localization algorithm system is designed to locate text in different kinds of images and eliminates the need to devise separate method for various kinds of images. Firstly, the color image is converted into grayscale image. After that, Haar Discrete Wavelet Transform (DWT) is employed. Haar DWT decompose image into four sub image coefficients, one is average and other three are detail. Now, Sobel edge detector is applied on three detail components, the resultant edges so obtained are combined to form edge map. The morphological dilation is performed on binary edge map and further label the connected components. Finally, using some specific condition, the text is obtained in bounding box.
A New Method of Image Compression Using Multi wavelet Technique with MFHWT and ROI in SPIHT
Shipra Gupta,,Chirag Sharma
International Journal of Innovative Technology and Exploring Engineering , 2012,
Abstract: In medical field the images produce by the modality is in the form of large file, in order to get the opinion from other doctors images are send using electronic media. As the file of images is very large to send, we require to have compression for images but with compression there is loss of information in the image. To minimize the loss and to increase the quality of image and requires compression is also to be done, wavelet transformation technology plays a vital role. So, in this paper we consider that multi wavelet with Region of Interest (ROI) selecting portion will not only give the quality but also reduce the loss of information from image. And we are going to implement the multi wavelet transformation with Modified Fast Haar Wavelet Transform (MFHWT) in Set Partitioning in Hierarchical Trees algorithm.
The Haar Wavelet Transform of a Dendrogram: Additional Notes  [PDF]
Fionn Murtagh
Computer Science , 2007,
Abstract: We consider the wavelet transform of a finite, rooted, node-ranked, $p$-way tree, focusing on the case of binary ($p = 2$) trees. We study a Haar wavelet transform on this tree. Wavelet transforms allow for multiresolution analysis through translation and dilation of a wavelet function. We explore how this works in our tree context.
Comparing Haar-Hilbert and Log-Gabor Based Iris Encoders on Bath Iris Image Database  [PDF]
Nicolaie Popescu-Bodorin,Valentina E. Balas
Computer Science , 2011, DOI: 10.1109/SOFA.2010.5565599
Abstract: This papers introduces a new family of iris encoders which use 2-dimensional Haar Wavelet Transform for noise attenuation, and Hilbert Transform to encode the iris texture. In order to prove the usefulness of the newly proposed iris encoding approach, the recognition results obtained by using these new encoders are compared to those obtained using the classical Log- Gabor iris encoder. Twelve tests involving single/multienrollment and conducted on Bath Iris Image Database are presented here. One of these tests achieves an Equal Error Rate comparable to the lowest value reported so far for this database. New Matlab tools for iris image processing are also released together with this paper: a second version of the Circular Fuzzy Iris Segmentator (CFIS2), a fast Log-Gabor encoder and two Haar-Hilbert based encoders.
Digital Watermarking System based on Cascading Haar Wavelet Transform and Discrete Wavelet Transform  [PDF]
Nidal F. Shilbayeh,Adham Alshamary
Journal of Applied Sciences , 2010,
Abstract: The aim of this study was to solve problems of modification, forgery, illegal manipulation and distribution of digital image, especially with the rapid growth of transmission techniques. Although, there are many ways to protect the images, the proposed system suggested a new technique to protect the image for the purposes of ownership, copyright and intellectual property. In this study, we present a new robust and secure hybrid watermarking technique based on Haar Wavelet Transformation (HWT) and Discrete Wavelet Transformation (DWT). The proposed method is constructed by cascading two different but complementary techniques: HWT and DWT wavelet transformations to provide a robust resistance to the protected image against different signal processing attacks. Adding a private key to the watermarking will increase the privacy and security, but by embedding watermark in that private key more protection in wavelet transform will result, leading to more resistant against attacks. The new technique has been proposed to solve the problem of illegal manipulation and distribution of digital image, i.e., HWT and DWT system. Performance evaluation of the proposed method showed improved results in terms of imperceptibility, robustness and security in comparison with others systems.
Chaotic trigonometric haar wavelet with focus on image encryption  [PDF]
Sodeif Ahadpour,Yaser Sadra
Computer Science , 2014,
Abstract: In this paper, after reviewing the main points of Haar wavelet transform and chaotic trigonometric maps, we introduce a new perspective of Haar wavelet transform. The essential idea of the paper is given linearity properties of the scaling function of the Haar wavelet. With regard to applications of Haar wavelet transform in image processing, we introduce chaotic trigonometric Haar wavelet transform to encrypt the plain images. In addition, the encrypted images based on a proposed algorithm were made. To evaluate the security of the encrypted images, the key space analysis, the correlation coefficient analysis and differential attack were performed. Here, the chaotic trigonometric Haar wavelet transform tries to improve the problem of failure of encryption such as small key space and level of security.
An Accelerate Algorithm on Fast Wavelet Transform for Signal Processing

LI Jian-ping,YAN Zhong-hong,ZHANG Wan-ping,

软件学报 , 2002,
Abstract: An method of analytic construction for wavelet filter coefficients is put forward, and the corresponding fast wavelet transform is set up. It is more oversimplified and more speedy than the famous Mallat algorithm. This method can be used adaptively to signal processing for choosing corresponding parameters of wavelet filter.
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