From cages to wedges and clefts : Design of some novel hosts based on Image , Image , Image -triquinane framework

Annulation of aromatic rings on the folded Image ,Image ,Image -triquinane backbone has led to the design of potential host systems Image and Image whose crystal structures have been determined.

Wavelet transform based error concealment approach for image denoising

Denoising of images in compressed wavelet domain has potential application in transmission technology such as mobile communication. In this paper, we present a new image denoising scheme based on restoration of bit-planes of wavelet coefficients in compressed domain. It exploits the fundamental property of wavelet transform - its ability to analyze the image at different resolution levels and the edge information associated with each band. The proposed scheme relies on the fact that noise commonly manifests itself as a fine-grained structure in image and wavelet transform allows the restoration strategy to adapt itself according to directional features of edges. The proposed approach shows promising results when compared with conventional unrestored scheme, in context of error reduction and has capability to adapt to situations where noise level in the image varies. The applicability of the proposed approach has implications in restoration of images due to noisy channels. This scheme, in addition, to being very flexible, tries to retain all the features, including edges of the image. The proposed scheme is computationally efficient.

Image reconstruction by inhomogeneous diffusion for positron emission tomography

In positron emission tomography (PET), image reconstruction is a demanding problem. Since, PET image reconstruction is an ill-posed inverse problem, new methodologies need to be developed. Although previous studies show that incorporation of spatial and median priors improves the image quality, the image artifacts such as over-smoothing and streaking are evident in the reconstructed image. In this work, we use a simple, yet powerful technique to tackle the PET image reconstruction problem. Proposed technique is based on the integration of Bayesian approach with that of finite impulse response (FIR) filter. A FIR filter is designed whose coefficients are determined based on the surface diffusion model. The resulting reconstructed image is iteratively filtered and fed back to obtain the new estimate. Experiments are performed on a simulated PET system. The results show that the proposed approach is better than recently proposed MRP algorithm in terms of image quality and normalized mean square error.

On resampling detection and its application to detect image tampering

Usually digital image forgeries are created by copy-pasting a portion of an image onto some other image. While doing so, it is often necessary to resize the pasted portion of the image to suit the sampling grid of the host image. The resampling operation changes certain characteristics of the pasted portion, which when detected serves as a clue of tampering. In this paper, we present deterministic techniques to detect resampling, and localize the portion of the image that has been tampered with. Two of the techniques are in pixel domain and two others in frequency domain. We study the efficacy of our techniques against JPEG compression and subsequent resampling of the entire tampered image.

GAP-RBF based NR image quality measurement for JPEG coded images

In this paper, we present a growing and pruning radial basis function based no-reference (NR) image quality model for JPEG-coded images. The quality of the images are estimated without referring to their original images. The features for predicting the perceived image quality are extracted by considering key human visual sensitivity factors such as edge amplitude, edge length, background activity and background luminance. Image quality estimation involves computation of functional relationship between HVS features and subjective test scores. Here, the problem of quality estimation is transformed to a function approximation problem and solved using GAP-RBF network. GAP-RBF network uses sequential learning algorithm to approximate the functional relationship. The computational complexity and memory requirement are less in GAP-RBF algorithm compared to other batch learning algorithms. Also, the GAP-RBF algorithm finds a compact image quality model and does not require retraining when the new image samples are presented. Experimental results prove that the GAP-RBF image quality model does emulate the mean opinion score (MOS). The subjective test results of the proposed metric are compared with JPEG no-reference image quality index as well as full-reference structural similarity image quality index and it is observed to outperform both.

Design of a FIR filter for image restoration using principal component neural networks

The neural network finds its application in many image denoising applications because of its inherent characteristics such as nonlinear mapping and self-adaptiveness. The design of filters largely depends on the a-priori knowledge about the type of noise. Due to this, standard filters are application and image specific. Widely used filtering algorithms reduce noisy artifacts by smoothing. However, this operation normally results in smoothing of the edges as well. On the other hand, sharpening filters enhance the high frequency details making the image non-smooth. An integrated general approach to design a finite impulse response filter based on principal component neural network (PCNN) is proposed in this study for image filtering, optimized in the sense of visual inspection and error metric. This algorithm exploits the inter-pixel correlation by iteratively updating the filter coefficients using PCNN. This algorithm performs optimal smoothing of the noisy image by preserving high and low frequency features. Evaluation results show that the proposed filter is robust under various noise distributions. Further, the number of unknown parameters is very few and most of these parameters are adaptively obtained from the processed image.

Real-time image denoising algorithm in teleradiology systems - art.no.606304

Denoising of medical images in wavelet domain has potential application in transmission technologies such as teleradiology. This technique becomes all the more attractive when we consider the progressive transmission in a teleradiology system. The transmitted images are corrupted mainly due to noisy channels. In this paper, we present a new real time image denoising scheme based on limited restoration of bit-planes of wavelet coefficients. The proposed scheme exploits the fundamental property of wavelet transform - its ability to analyze the image at different resolution levels and the edge information associated with each sub-band. The desired bit-rate control is achieved by applying the restoration on a limited number of bit-planes subject to the optimal smoothing. The proposed method adapts itself to the preference of the medical expert; a single parameter can be used to balance the preservation of (expert-dependent) relevant details against the degree of noise reduction. The proposed scheme relies on the fact that noise commonly manifests itself as a fine-grained structure in image and wavelet transform allows the restoration strategy to adapt itself according to directional features of edges. The proposed approach shows promising results when compared with unrestored case, in context of error reduction. It also has capability to adapt to situations where noise level in the image varies and with the changing requirements of medical-experts. The applicability of the proposed approach has implications in restoration of medical images in teleradiology systems. The proposed scheme is computationally efficient.

A new FIR filter for image restoration

Image filtering techniques have potential applications in biomedical image processing such as image restoration and image enhancement. The potential of traditional filters largely depends on the apriori knowledge about the type of noise corrupting the image. This makes the standard filters to be application specific. For example, the well-known median filter and its variants can remove the salt-and-pepper (or impulse) noise at low noise levels. Each of these methods has its own advantages and disadvantages. In this paper, we have introduced a new finite impulse response (FIR) filter for image restoration where, the filter undergoes a learning procedure. The filter coefficients are adaptively updated based on correlated Hebbian learning. This algorithm exploits the inter pixel correlation in the form of Hebbian learning and hence performs optimal smoothening of the noisy images. The application of the proposed filter on images corrupted with Gaussian noise, results in restorations which are better in quality compared to those restored by average and Wiener filters. The restored image is found to be visually appealing and artifact-free

Wavelet transform based error concealment approach for image denoising

Denoising of images in compressed wavelet domain has potential application in transmission technology such as mobile communication. In this paper, we present a new image denoising scheme based on restoration of bit-planes of wavelet coefficients in compressed domain. It exploits the fundamental property of wavelet transform - its ability to analyze the image at different resolution levels and the edge information associated with each band. The proposed scheme relies on the fact that noise commonly manifests itself as a fine-grained structure in image and wavelet transform allows the restoration strategy to adapt itself according to directional features of edges. The proposed approach shows promising results when compared with conventional unrestored scheme, in context of error reduction and has capability to adapt to situations where noise level in the image varies. The applicability of the proposed approach has implications in restoration of images due to noisy channels. This scheme, in addition, to being very flexible, tries to retain all the features, including edges of the image. The proposed scheme is computationally efficient.

Examination of the role of follicle stimulating hormone in estrogen biosynthesis Image Image and Image Image in the ovary of cyclic hamster

The effect of neutralizing endogenous follicle stimulating hormone (FSH) or luteinizing hormone (LH) with specific antisera on the Image Image and Image Image synthesis of estrogen in the ovary of cycling hamster was studied. Neutralization of FSH or LH on proestrus resulted in a reduction in the estradiol concentration of the ovary on diestrus-2 and next proestrus, suggesting an impairment in follicular development.Injection of FSH antiserum at 0900 h of diestrus-2 significantly reduced the ovarian estradiol concentration within 6–7 h. Further, these ovaries on incubation with testosterone(T) Image Image at 1600 h of the same day or the next day synthesized significantly lower amounts of estradiol, compared to corresponding control ovaries. Although testosterone itself, in the absence of endogenous FSH, could stimulate estrogen synthesis to some extent, FSH had to be supplemented with T to restore estrogen synthesis to the level seen in control ovaries incubated with T. Lack of FSH thus appeared to affect the aromatization step in the estrogen biosynthetic pathway in the ovary of hamster on diestrus-2. In contrast to this, FSH antiserum given on the morning of proestrus had no effect on the Image Image and Image Image synthesis of estrogen, when examined 6–7 h later. The results suggest that there could be a difference in the need for FSH at different times of the cycle.Neutralization of LH either on diestrus-2 or proestrus resulted in a drastic reduction in estradiol concentration of the ovary. This block was at the level of androgen synthesis, since supplementing testosterone alone Image Image could stimulate estrogen synthesis to a more or less similar extent as in the ovaries of control hamsters.

A novel two sources ultrasound modulated optical tomographic system for screening breast cancer through elasticity characterization

The study of non-invasive characterization of elastic properties of soft biological tissues has been a focus of active researches since recent years. Light is highly scattered by biological tissues and hence, sophisticated reconstruction algorithms are required to achieve good imaging depth and a reasonable resolution. Ultrasound (US), on the otherhand, is less scattered by soft tissues and it has been in use for imaging in biomedical ultrasound systems. Combination of the contrast sensitivity of light and good localization of ultrasound provides a challenging technique for characterization of thicker tissues deep inside the body non-invasively. The elasticity of the tissues is characterized by studying the response of tissues to mechanical excitation induced by an acoustic radiation force (remotely) using an optical laser. The US modulated optical signals which traverse the tissue are detected by using a CCD camera as detector array and the pixel map formed on the CCD is used to characterize the embedded inhomogeneities. The use of CCD camera improves the signal-noise-ratio (SNR) by averaging the signals from all of the CCD pixels.

Effect of interaction of macrocracks on the stress intensity factor in a beam

Beams with a central edge crack, as well as other noncentral vertical and inclined edge cracks distributed symmetrically, subjected to three-point as well as four-point bending, are analysed using the finite element technique. Values of stress intensity factor K1 at the central crack tip for a crack-to-beam depth ratio Image equal to 0.5, are calculated for various cracked-beam configurations, using the compliance calibration technique as well as method of strain energy release rate. These are compared with the value of K1 for the case of a beam with central edge crack alone. Results of the present parametric study are used to specify the range of values pertaining to basic parameters such as crack-to-beam depth ratios, geometry and position with respect to central edge crack, of other macrocracks for which interaction exists. Accordingly, the macrocracks are classified as either interacting or noninteracting types. Hence for noninteracting types of cracks, analytical expressions available for the determination of K1 in the case of beam with a central edge crack alone, are applicable.

Contribution of sea-salt to aerosol optical depth over the Arabian Sea derived from MODIS observations

Making use of aerosol optical depths (AOD) derived from MODIS (onboard TERRA satellite) and winds from NCEP, and the fact that sea-salt optical depth over ocean is determined primarily by sea-surface wind speed, we examine the contribution of sea-salt to the composite aerosol optical depth ( AOD) over Arabian Sea ( AS), by developing empirical models for characterizing wind-speed dependence of sea-salt optical depth. We show that at high wind speeds, sea-salt contributes 81% to the coarse mode and 42% to the composite AOD in the southern AS. In contrast to this, over the northern AS, share of sea-salt to coarse mode and composite optical depth is only 35% and 16% respectively. Comparison of the sea-salt optical depth and coarse mode optical depth ( MODIS) showed excellent agreement. The sea-salt optical depth over AS at moderate to high wind speed is comparable to the anthropogenic AOD reported for this region during winter.

Simultaneous display of image and spectrum in the same plane: a generalized analysis

A generalized analysis, using the Vander Lugt operational notation, of the building block optical system comprising a single holographic optical element (HOE) for achieving simultaneous display of the spectrum and the image of an object in a single plane, has been carried out. The salient features of this analysis are: (1) it allows comprehensive characterization of the HOE, (2) it provides insights into the many possible configurations for the system, and (3) it explains the existing results in a consistent manner.