Introduction In this tutorial, we will implement the Deep CNN-Based Blind Image Quality Predictor (DIQA) methodology proposed by Jongio Kim, Anh-Duc Nguyen, and Sanghoon Lee [1]. Also, I will go through the following TensorFlow 2.0 concepts: Download and prepare a dataset using a tf.data.Dataset builder. Define a TensorFlow input pipeline to…

Introduction As visual creatures, humans are sensitive to visual signal impairments such as blockiness, blurriness, noisiness, and transmission loss. Thus, I have focused my research on finding how image quality affects user behavior in web applications. Lately, several studies test the effect of low-quality images on web sites. Cornell University [4]…

Some months ago, I decided to buy a new laptop with enough power to crunch data. At that time, I also had a desktop with a GTX 1070, but I stopped using it because of the convenience of my new laptop. Having a GPU like the GTX 1070 dusting is…

Image quality is a notion that highly depends on observers. Generally, it is linked to the conditions in which it is viewed; therefore, it is a highly subjective topic. Image quality assessment aims to quantitatively represent the human perception of quality. …