Image quality assessment is a difficult problem in the field of image processing without any acceptable solution yet. Quality assessment of textures, which is the topic of this work, is even harder problem. This work presents an overview and a description of current state of the art methods as well as brief experiments on textures and a discussion about the usability of these methods on textures.

The image content detectability and image structure preservation are closely related concepts with undeniable role in image quality assessment. However, the most attention of image quality studies has been paid to image structure evaluation, few of them focused on image content detectability. Examining the image structure was firstly introduced and assessed in Structural SIMilarity (SSIM) measu...

The current methods of turfgrass evaluations are often based on human-based assessment methods. However, eliminating subjective errors from such evaluations is often impossible. This research compared the accuracy of human-based and digital image processing-based methods for quality assessment of turfgrasses. Four turfgrass plots were evaluated using the two mentioned methods. In the human-base...

Growth in digital image processing technologies have completely change our way of life. In our day-to-day life, we are using a number of image processing applications knowingly or unknowingly. Many times image gets distorted somehow during the acquisition, processing, transmission, storing or sharing. So the evaluation of image quality is essential component for many image processing applicatio...

The current methods of turfgrass evaluations are often based on human-based assessment methods. However, eliminating subjective errors from such evaluations is often impossible. This research compared the accuracy of human-based and digital image processing-based methods for quality assessment of turfgrasses. Four turfgrass plots were evaluated using the two mentioned methods. In the human-base...

Automatic image quality assessment has many diverse applications. Existing quality measures are not accurate representatives of the human perception. We present a hybrid image quality (HIQ) measure, which is a combination of four existing measures using an ‘n’ degree polynomial to accurately model the human image perception. First we undertook time consuming human experiments to subjectively ev...

Present quality assessment (QA) algorithms aim to generate scores for natural images consistent with subjective scores for the quality assessment task. For the quality assessment task, human observers evaluate a natural image based on its perceptual resemblance to a reference. Natural images communicate useful information to humans, and this paper investigates the utility assessment task, where...