Image Quality Assessment using Deep Learning Methodology

  • Balakrishnan Natarajan, Vanitha Alagesan


In the real world image places a major role of our human life. Now a days, many images are captured using the smart devices like mobile, tablets, scanners and image capturing cameras. Images play a major role in the fields like medical, designing, visualization of the products and etc. In which these images are to be assessed for its quality. Many researches are carried out to verify the quality of the images. The quality of image can be assessed by deep learning. The features are extracted and assessed using Feed Forward network. The Feed Forward network assess the images from the output of the previous layer. The analysis is done on the feature like noise, luminance, and edge pixels. These features are identified and analyzed with lower time on the factor average processing time. The experimental result shows that the image quality is assessed with minimum time comparing withFUIQA, HE-HALR which yields better result.

How to Cite
Balakrishnan Natarajan, Vanitha Alagesan. (2020). Image Quality Assessment using Deep Learning Methodology. International Journal of Advanced Science and Technology, 29(04), 7353 -. Retrieved from