Change detection based on satellite images acquired from an area at different dates is of widespread interest, according to the increasing number of flood-related disasters. The images help to generate products that support emergency response and flood management at a global scale. In this paper, a novel unsupervised change detection approach based on image fusion is introduced. The approach ai...

Breast cancer is the most prevalent among women, and diagnosing it early vital for successful treatment. The examination of images captured during biopsies plays an important role in determining whether a patient has or not. However, stochastic patterns, varying intensities colors, large sizes these make challenging to identify mark malignant regions them. Against this backdrop, study proposes ...

Thermal data products derived from remotely sensed data play significant roles as key parameters for biophysical phenomena. However, a trade-off between spatial and spectral resolutions has existed in thermal infrared (TIR) remote sensing systems, with the end product being the limited resolution of the TIR sensor. In order to treat this problem, various disaggregation methods of TIR data, base...

Many algorithms have been developed to find sparse representation over redundant dictionaries or transform. This paper presents a novel method on compressive sensing (CS)-based image compression using sparse basis on CDF9/7 wavelet transform. The measurement matrix is applied to the three levels of wavelet transform coefficients of the input image for compressive sampling. We have used three di...

Nowadays digital image compression and decompression techniques are very much important. So our aim is to calculate the quality of face and other regions of the compressed image with respect to the original image. Image segmentation is typically used to locate objects and boundaries (lines, curves etc.)in images. After segmentation the image is changed into something which is more meaningful to...

In the paper a probabilistic approach to quality assessment of image processing algorithms is proposed. Presented scalar measure can be used for any colour space and gives very similar results regardless on the image content. It can be an interesting supplement to existing image quality metrics in applications where the details of the processing algorithm are known. Its good correlation with su...

We propose a universal no-reference (NR) image quality assessment (QA) index that does not require training on human opinion scores. The new index utilizes perceptually relevant image features extracted from the distorted image. These include the mean phase con-gruency (PC) of the image, the entropy of the phase congruencyPC image, the entropy of the distorted image, and the mean gradient magni...

abtract background: in nuclear medicine, phantoms are mainly used to evaluate the overall performance of the imaging systems and practically there is no phantom exclusively designed for the evaluation of the software performance.  in this study the hoffman brain phantom was used for quantitative evaluation of reconstruction techniques. the phantom is modified to acquire tomographic and planar i...

introduction: attenuation correction is a useful process for improving myocardial perfusion spect and is dependent on activity and distribution of attenuation coefficients in the body (attenuation map). attenuation artifacts are a common problem in myocardial perfusion spect. the aim of this study was to compare the effect of attenuation correction using different attenuation maps and different...