%0 Journal Article %1 noauthororeditor %A Bhor, Pooja %A Gargote, Rupali %A Vhorkate, Rupali %A Yawle, R. U. %A Bairagi, V. K. %D 2013 %E Kumar, Dr. Shiv %J International Journal of Innovative Science and Modern Engineering (IJISME) %K blur detection images images. no-reference noisy probability sharp %N 5 %P 76-80 %T A No Reference Image Blur Detection using Cumulative probability Blur Detection (CPBD) Metric %U https://www.ijisme.org/wp-content/uploads/papers/v1i5/E0209041513.pdf %V 1 %X This work presents a perceptual-based noreference objective image sharpness/blurriness metric by integrating the concept of cumulative probability blur detection with the just noticeable blur into a probability summation model. Unlike existing objective no-reference image sharpness / blurriness metrics, the proposed metric is able to predict the relative amount of blurriness in images with different content. Results are provided to illustrate the performance of the proposed perceptualbased sharpness metric. The blur perception information at each edge is then pooled over the entire image to obtain a final quality score by evaluating the cumulative probability of blur detection (CPBD) metric. Higher metric value represent sharper image. Images having small metric value denote blurred and noisy images .The main purpose of CPBD metric is in TELEMEDICINE and Image quality Measure.

@article{noauthororeditor, abstract = {This work presents a perceptual-based noreference objective image sharpness/blurriness metric by integrating the concept of cumulative probability blur detection with the just noticeable blur into a probability summation model. Unlike existing objective no-reference image sharpness / blurriness metrics, the proposed metric is able to predict the relative amount of blurriness in images with different content. Results are provided to illustrate the performance of the proposed perceptualbased sharpness metric. The blur perception information at each edge is then pooled over the entire image to obtain a final quality score by evaluating the cumulative probability of blur detection (CPBD) metric. Higher metric value represent sharper image. Images having small metric value denote blurred and noisy images .The main purpose of CPBD metric is in TELEMEDICINE and Image quality Measure.}, added-at = {2021-09-22T13:34:42.000+0200}, author = {Bhor, Pooja and Gargote, Rupali and Vhorkate, Rupali and Yawle, R. U. and Bairagi, V. K.}, biburl = {https://www.bibsonomy.org/bibtex/2986e7b20de55d249da48541a26b0f1cf/ijisme_beiesp}, editor = {Kumar, Dr. Shiv}, interhash = {4122057c51d67034787548f38230e6dd}, intrahash = {986e7b20de55d249da48541a26b0f1cf}, issn = {2319-6386}, journal = {International Journal of Innovative Science and Modern Engineering (IJISME)}, keywords = {blur detection images images. no-reference noisy probability sharp}, language = {En}, month = {April}, number = 5, pages = {76-80}, timestamp = {2021-09-22T13:34:42.000+0200}, title = {A No Reference Image Blur Detection using Cumulative probability Blur Detection (CPBD) Metric}, url = {https://www.ijisme.org/wp-content/uploads/papers/v1i5/E0209041513.pdf}, volume = 1, year = 2013 }