Image quality assessment has a great importance in several image processingapplications. Recently, various objective image quality metrics have been proposed in order topredict the human visual perception. In this paper, novel image quality metrics, S-SSIM(saliency-based structural similarity index) and S-VIF (saliency-based visual informationfidelity), are proposed based on fre...

Image quality assessment (IQA) is a crucial technique in perceptual image/video coding, because it is not only a ruler for performance evaluation of coding algorithms but also a metric for ratio-distortion optimization in coding. In this paper, inspired by the fact that distortions of both global and local information influence the perceptual image quality, we propose a novel IQA method that in...

Interpretive structural modelling (ISM) is a well-established methodology for identifying relationships among specific items, which define a problem or an issue. This approach has been increasingly used by various researchers to represent the interrelationships among various elements related to the issue. ISM approach starts with an identification of variables, which are relevant to the problem...

We present a distributed component-object model (DCOM) based single system image middleware (SSIM) for metacomputer implementation of genetic programming (MIGP). MIGP is aimed to significantly improve the computational performance of genetic programming (GP) exploiting the inherent parallelism in GP among the evaluation of individuals. It runs on costeffective clusters of commodity, non-dedicat...

The medical field along with computer field grows in a rapid manner. In telemedicine and telediagnosis authentication of medical images are very important to the patient ,doctor and Insurance company. The youngsters are also keen in knowing about the treatment methods and procedures. But no one likes to tell about the disease in open hall. So there is always an urge for watermarking of medical ...

In this work we determine how well the common objective image quality measures (Mean Squared Error (MSE), local MSE, Signalto-Noise Ratio (SNR), Structural Similarity Index (SSIM), Visual Signalto-Noise Ratio (VSNR) and Visual Information Fidelity (VIF)) predict subjective radiologists’ assessments for brain and body computed tomography (CT) images. A subjective experiment was designed where ra...

In this paper, we propose a novel image quality assessment (IQA) based on an Improved Structural SIMilarity (ISSIM) which considers the spatial distributions of image structures. The existing structural similarity (SSIM) metric, which measures structure loss based on statistical moments, i.e., the mean and variance, represents mainly the luminance change of pixels rather than describing the spa...

A large fraction of the current Internet traffic is caused by video streaming. Due to the growing expectations of video consumers, monitoring video applications is getting more and more important for network and service providers. In a previous work, we proposed a video quality monitoring solution which utilizes the full reference SSIM metric to improve the monitoring in the network by distribu...

We propose a method for lossy image compression based on recurrent, convolutional neural networks that outperforms BPG (4:2:0), WebP, JPEG2000, and JPEG as measured by MS-SSIM. We introduce three improvements over previous research that lead to this state-of-the-art result. First, we show that training with a pixel-wise loss weighted by SSIM increases reconstruction quality according to several...

The basic requisites for any steganography algorithm include imperceptibility, embedding capacity and robustness to communication attacks. To measure the quality of gray-scale or color image, the metric such as PSNR is widely used by researchers in steganography. However, for digital color image, there are many other options such as WPSNR, PSNRE, PSNRY, PSNR-HSR, CQM etc. In this paper, we have...