Image interpolation using Shearlet based iterative refinement

This paper proposes an image interpolation algorithm exploiting sparse representation for natural images. It involves three main steps: (a) obtaining an initial estimate of the high resolution image using linear methods like FIR filtering, (b) promoting sparsity in a selected dictionary through iterative thresholding, and (c) extracting high frequency information from the approximation to refine the initial estimate. For the sparse modeling, a shearlet dictionary is chosen to yield a multiscale directional representation. The proposed algorithm is compared to several state-of-the-art methods to assess its objective as well as subjective performance. Compared to the cubic spline interpolation method, an average PSNR gain of around 0.8 dB is observed over a dataset of 200 images

Study on high Performance and Effective Watermarking Scheme using Hybrid Transform (DCT-DWT)

Nowadays healthcare infrastructure depends on Hospital Information Systems (HIS), Radiology Information Systems (RIS),Picture archiving and Communication Systems (PACS) as these provide new ways to store, access and distribute medical data . It eliminates the security risk. Conversely, these developments have introduced new risks for unsuitable deployment of medical information flowing in open networks, provided the effortlessness with which digital content can be manipulated. It is renowned that the integrity and confidentiality of medical data is a serious topic for ethical and legal reasons. Medical images need to be kept intact in any condition and prior to any operation as well need to be checked for integrity and verification. Watermarking is a budding technology that is capable of assisting this aim. In recent times, frequency domain watermarking algorithms have gained immense importance due to their widespread use. Subsequently, the watermark embedding and extraction are performed in frequency domain using the presented scheme. The proposed watermarking scheme, the watermark extraction compared with the original image for calculating SSIM.The effectiveness of the proposed watermarking scheme is demonstrated with the aid of experimental results

A Survey on Techniques to Protect Video files Using Watermarking

In this advanced age the principle issue with multimedia documents like picture and video is theft. The Radical increment in trades of information over the web and the incessant utilization of advanced medium has been watched. Computerized data can be shielded from unapproved get to and sharing through watermarking. Digital watermarking is the methodology of inserting some applicable data in the host signal. With the utilization of watermarking systems on unique medium, licensed innovation rights can be saved over web. An investigation deals with various elements and techniques for computerized watermarking has been carried out and introduced in this paper

Reliable and Efficient coding Technique for Compression of Medical Images based on Region of Interest using Directional Filter Banks

Medical images carry huge and vital information. It is necessary to compress the medical images without losing its vital-ness. The proposed algorithm presents a new coding technique based on  image compression using contourlet transform used in different modalities of medical imaging. Recent reports on natural image compression have shown superior performance of contourlet transform, a new extension to the wavelet transform in two dimensions using nonseparable and directional filter banks. As far as medical images are concerned the diagnosis part (ROI) is of much important compared to other regions. Therefore those portions are segmented from the whole image using  fuzzy C-means(FCM) clustering technique. Contourlet transform is then applied to ROI portion which performs Laplacian Pyramid(LP) and Directional Filter Banks. The region of less significance are compressed using Discrete Wavelet Transform and finally modified embedded zerotree wavelet algorithm is applied which uses six symbols instead of four symbols used in Shapiro’s EZW to the resultant image which shows better PSNR and high compression ratio.Â

Multiscale texture descriptors for automatic small bowel tumors detection in capsule endoscopy

Conventional endoscopic exams do not allow the entire visualization of the gastrointestinal (GI) tract. Push enteroscopy (PE) is an effective diagnostic and therapeutic procedure, although it only allows exploration of the proximal small bowel (Pennazio et al., 1995). Simultaneously, convetional colonoscopy is limited at the terminal ileum. Therefore, prior to the wireless capsule endoscopy era, the small intestine was the conventional endoscopy’s last frontier, because it could not be internally visualized directly or in it’s entirely by any method (Herrerías & Mascarenhas-Saraiva, 2007). The small intestine accounts for 75% of the total length and 90% of the surface area of the gastrointestinal tract. In adults it measures about 570 cm at post mortem, which is substantially longer than conventional video endoscopes (100-180 cm) (Swain & Fritscher-Ravens, 2004). Intraoperative enteroscopy is the most complete but also the most invasive means of examining the small bowel (Gay et al., 1998). Given the technical and medical improvements introduced on the assessment of the gastrointestinal (GI) tract, Capsule Endoscopy (CE) is considered as the first major technological innovation in GI diagnostic medicine since the flexible endoscope (Kaffes, 2009). More recently, a new technique, the double-balloon enteroscopy (DBE), has been introduced into clinical practice (Yamamoto & Kita, 2006). DBE has the potential to examine the entire length of the small bowel with biopsy and therapeutic capability. Nevertheless, it is a time consuming procedure that requires specialist training for the operating physician. We should note that DBE and CE are complementary tools and not competitive (Chen et al., 2007). Hence, the diagnostic ease of CE can be complemented with a targeted and often therapeutic DBE (Kaffes, 2009). Therefore, CE can be used as a first line diagnosis method, while DBE can be used as a confirmatory or therapeutic modality for lesions first visualized by CE (Pennazio, 2006). The endoscopic capsule is a pill-like device, with only 11mm x 26 mm, and includes a miniaturized camera, a light source and circuits for the acquisition and wireless transmission of signals (Iddan et al., 2000). As the capsule moves through GI tract, propelled exclusively by peristalsis, it acquires images at a rate of two per second and sends them to a hard disk receiver that is worn in the belt of the patient, in a wireless communication scheme. The acquisition of images is limited by the battery life of the device, usually around eight hours, which imply that in a single CE exam more than 50000 images are acquired. If no complications arise, the capsule should be in the patient’s stool, usually within 24-48 h, and not reused (Pennazio, 2006). Capsule endoscopy has evolved in a few short years to become a first-line, noninvasive diagnostic technique for the small bowel. CE is now being utilized worldwide to assess patients for obscure gastrointestinal bleeding, possible Crohn’s disease, celiac disease and small bowel tumors (Lee & Eisen, 2010). It is now available in over 4500 practice sites around the world (Munoz-Navas, 2009). The time required to a physician to analyze the resulting video is, on average, 40-60 min (Pennazio, 2006). The reading time and interpretation of CE exams is very time consuming given that more than 50,000 images have to be reviewed (Delvaux & Gay, 2006; Mergener et al., 2007), which contributes to the high cost of a CE exam (Westerhof et al., 2009). Thus, a computer assisted diagnosis tool to help the physicians to evaluate CE exams faster and more accurately is an important technical challenge and an excellent economical opportunity.Centre Algoritm

Text Hiding in Coded Image Based on Quantization Level Modification and Chaotic Function

A text hiding method in codded image is presented in this paper that based on quantization level modification. The used image is transformed into wavelet domain by DWT and coefficient of transform is partitioned into predefined block size. Specific threshold has been used to classify these blocks into two types named smooth and complex. Each type has its own method of text hiding (binary data), for smooth blocks, secret bits which represent the text data are switched by the bitmap. In order to reduce distortion, the quantization levels are modified. To reach extra embedding payload the quantization level could carry extra two bits depending on other threshold. The complex block carry one data bit on each block and quantization levels are swapped to reduce distortion with bitmap flipping. The proposed method result shows a high signal to noise ratio, with studying capacity as important in this work

A novel fast and reduced redundancy structure for multiscale directional filter banks

2007-2008 > Academic research: refereed > Publication in refereed journalVersion of RecordPublishe

Enhancement of Single and Composite Images Based on Contourlet Transform Approach

Image enhancement is an imperative step in almost every image processing algorithms. Numerous image enhancement algorithms have been developed for gray scale images despite their absence in many applications lately. This thesis proposes hew image enhancement techniques of 8-bit single and composite digital color images. Recently, it has become evident that wavelet transforms are not necessarily best suited for images. Therefore, the enhancement approaches are based on a new 'true' two-dimensional transform called contourlet transform. The proposed enhancement techniques discussed in this thesis are developed based on the understanding of the working mechanisms of the new multiresolution property of contourlet transform. This research also investigates the effects of using different color space representations for color image enhancement applications. Based on this investigation an optimal color space is selected for both single image and composite image enhancement approaches. The objective evaluation steps show that the new method of enhancement not only superior to the commonly used transformation method (e.g. wavelet transform) but also to various spatial models (e.g. histogram equalizations). The results found are encouraging and the enhancement algorithms have proved to be more robust and reliable

The nonredundant contourlet transform (NRCT): a multiresolution and multidirection image representation with perfect reconstruction property

Multiresolution and multidirection image representation has recently been an attractive research area, in which multiresolution corresponds to varying scale of structure in images, while multidirection deals with the oriented nature of image structure. Numerous new systems, such as the contourlet transform, have been developed. The contourlet transform has the benefit of efficiently capturing the oriented geometrical structures of images; however, it has the drawback of a 4/3 redundancy in its oversampling ratio. In order to eliminate the redundancy, this thesis proposes a progressive version of the contourlet transform which can be calculated with critical sampling. The new proposed image representation is called the nonredundant contourlet transform (NRCT), which is constructed with an efficient framework of filter banks. In addition to critical sampling, the proposed NRCT possesses many valuable properties including perfect reconstruction, sparse expression, multiresolution, and multidirection. Numerical experiments demonstrate that the novel NRCT has better peak signal-to-noise performance than the traditional contourlet transform. Moreover, for low ratios of retained coefficients, the NRCT outperforms the wavelet transform which is a standard method for the critically sampled representation of images. -- After examining the computational complexity of the nonredundant contourlet transform, this thesis applies the NRCT to fingerprint image compression, since fingerprint images are examples of images with oriented structures. Based on an appropriately designed filter bank structure, the NRCT is easily compatible with the wavelet transform. Hence a new transform is created called the semi-NRCT, which takes the advantages of the directional selectivity of the NRCT and the lower complexity of the wavelet transform. Finally, this thesis proposes a new fingerprint image compression scheme based on the semi-NRCT. The semi-NRCT-based fingerprint image compression is compared with other transform-based compressions, for example the wavelet-based and the contourlet-based algorithms, and is shown to perform favorably