Correction to: Structural Toughness Under Noise: An Efficient No-Reference Image Distortion Assessment for Blur and Noise

No-Reference Image Quality Assessment using Blur and Noise

Assessment for image quality traditionally needs its original image as a reference. The conventional method for assessment like Mean Square Error (MSE) or Peak Signal to Noise Ratio (PSNR) is invalid when there is no reference. In this paper, we present a new No-Reference (NR) assessment of image quality using blur and noise. The recent camera applications provide high quality images by help of...

No-reference assessment of blur and noise impacts on image quality

The quality of images may be severely degraded in various situations such as imaging during motion, sensing through a diffusive medium, and low signal to noise. Often in such cases, the ideal un-degraded image is not available (no reference exists). This paper overviews past methods that dealt with no-reference (NR) image quality assessment, and then proposes a new NR method for the identificat...

No-Reference Noise and Blur Detection via the Fourier Transform

This research presents a new method of distinguishing between noisy, blurred and otherwise uncorrupted images via the Fourier transform. The spectrum of an image corrupted by noise is markedly different from one that is marred by blurring, or one that is not damaged at all. In particular, there are more high frequency terms in the spectrum of a noisy image than in that of a blurred image, and, ...

No-reference Video Quality Assessment for Noise, Blur, and MPEG2 Natural Videos

In this paper, we propose a new no-reference VQA metric, called Video Hybrid No-reference (VHNR) method. It is based on natural video statistics built from the coefficients of 3D curvelet and cosine transforms. VHNR can blindly predict the quality of noisy, blurry, or MPEG2 compressed videos and requires no original reference video. The 3D curvelet transform is known to be sensitive to surface ...

Non-reference assessment of sharpness in blur/noise degraded images