This paper proposes new and original adaptive image ringing detection and ringing suppression methods. Ringing detection is performed using a scale-space based computational analysis of ideal low-pass filtering of step edges. Edge width conception is introduced and is used to approximate ringing parameter. Method to choose strong isolated edges which are the best suitable edges for ringing anal...

OBJECTIVE To determine the incidence, aeriology, and outcome of injuries due to bell ringing. DESIGN Retrospective review of the last six years' issues of Ringing World, advertisement in Ringing World, and a postal questionnaire sent to 20 active ringing towers. SUBJECTS Regular bell ringers. RESULTS Seventy nine injuries were identified both from review and by advertisement in Ringing Wo...

Ringing artifacts arise near edges in highly compressed JPEG2000 images. This paper proposes original image ringing detection and suppression techniques. On the first stage edge detection and ringing estimation algorithms are applied to calculate the ringing map of a compressed input image. On the second stage this ringing map is utilized to adjust the smart bilateral filter for effectively pro...

An efficient approach toward a no-reference ringing metric intrinsically exists of two steps: first detecting regions in an image where ringing might occur, and second quantifying the ringing annoyance in these regions. This paper presents a novel approach toward the first step: the automatic detection of regions visually impaired by ringing artifacts in compressed images. It is a noreference a...

JPEG2000 plays an important role in image data compression. However, JPEG-2000 produces noticeable image degradation, so-called “ringing artifacts,” in the vicinities of edges in reconstructed images, especially when the images are highly compressed. Ringing artifacts result in artificial contours, thus so degrading the quality of decoded images. To improve the visual quality of decoded images ...

In this work we propose a subjective no reference ringing metric using machine learning techniques. For every block in a JPEG compressed image the algorithm outputs a value which corresponds to the annoyance of the ringing artifacts. The extracted feature vector is designed bearing in mind the properties of the HVS (Human Visual System) and the ringing artifacts. The presented results show succ...