Ihor Olehovych Kirenko

Coding Artifact Reduction Based on Local Entropy Analysis

Coding artifacts are very annoying in highly compressed images and video sequences. Most artifact reduction techniques blur the details of the images while removing various coding artifacts. In this paper, we propose a novel and explicit approach for classifying blocks into detailed regions, intermediate regions and smooth regions. The classification is based on the information content of the underlying region. The information content of a region is quantized by local entropy, which is calculated on the PDF of the pixel intensity distribution. Local entropy is used as an indicator of how much smoothing is needed for a certain region. It is well known that blocking artifacts are more visible in flat regions than in detailed regions. We apply mild low-pass filters on detailed regions to preserve the sharpness, and strong low-pass filters on flat regions to remove the severe blocking artifacts. Experimental results show that our proposed algorithm can preserve the details and reduce coding artifacts better than more expensive state of the art techniques .

Coding Artifact Reduction using Non-Reference Block Grid Visibility Measure

In this work a new method is proposed for coding artifact reduction of MPEG compressed video sequences. The method makes use of a simple cost-effective technique that allows the block grid position and its visibility to be determined without the need for access to the coding parameters. This information, combined with the results of local spatial analysis of luminance and chrominance components of a decoded image, is used to effectively suppress coding artifacts while preserving the sharpness of object edges. Results of our experiments confirm the high efficiency of the proposed approach

Quality adaptive least squares trained filters for video compression artifacts removal using a no-reference block visibility metric

Compression artifacts removal is a challenging problem because videos can be compressed at different qualities. In this paper, a least squares approach that is self-adaptive to the visual quality of the input sequence is proposed. For compression artifacts, the visual quality of an image is measured by a no-reference block visibility metric. According to the blockiness visibility of an input image, an appropriate set of filter coefficients that are trained beforehand is selected for optimally removing coding artifacts and reconstructing object details. The performance of the proposed algorithm is evaluated on a variety of sequences compressed at different qualities in comparison to several other de-blocking techniques. The proposed method outperforms the others significantly both objectively and subjectively.

Reduction of coding artifacts using chrominance and luminance spatial analysis

This paper presents a new low-cost method for coding artifact reduction of MPEG compressed video sequences. The algorithm detects possible locations of blocking and ringing artifacts by analyzing local spatial activity of luminance and chrominance components. The analysis explores differences in processing of luminance and chrominance during video coding. Depending on the outcomes of the analysis, one of three low-pass filters is applied. The results of our experiments show the high efficiency of the proposed approach.

Quality adaptive trained filters for compression artifacts removal

A compression artifacts removal algorithm that is adaptive to the artifact visibility level of the input video signal is proposed. The artifact visibility is determined per frame by the ratio of the accumulated gradient on the block edges to that of the remaining area. The filtering of each video frame is optimized using a least mean square mechanism which trains on pairs of target images and decompressed images of similar quality as the input frame. Experimental results show that the proposed approach outperforms several methods in coding artifact reduction.

Calibration of Contactless Pulse Oximetry.

BACKGROUND: Contactless, camera-based photoplethysmography (PPG) interrogates shallower skin layers than conventional contact probes, either transmissive or reflective. This raises questions on the calibratability of camera-based pulse oximetry. METHODS: We made video recordings of the foreheads of 41 healthy adults at 660 and 840 nm, and remote PPG signals were extracted. Subjects were in normoxic, hypoxic, and low temperature conditions. Ratio-of-ratios were compared to reference SpO2 from 4 contact probes. RESULTS: A calibration curve based on artifact-free data was determined for a population of 26 individuals. For an SpO2 range of approximately 83% to 100% and discarding short-term errors, a root mean square error of 1.15% was found with an upper 99% one-sided confidence limit of 1.65%. Under normoxic conditions, a decrease in ambient temperature from 23 to 7°C resulted in a calibration error of 0.1% (±1.3%, 99% confidence interval) based on measurements for 3 subjects. PPG signal strengths varied strongly among individuals from about 0.9 × 10−3 to 4.6 × 10−3 for the infrared wavelength. CONCLUSIONS: For healthy adults, the results present strong evidence that camera-based contactless pulse oximetry is fundamentally feasible because long-term (eg, 10 minutes) error stemming from variation among individuals expressed as A*rms is significantly lower (<1.65%) than that required by the International Organization for Standardization standard (<4%) with the notion that short-term errors should be added. A first illustration of such errors has been provided with A**rms = 2.54% for 40 individuals, including 6 with dark skin. Low signal strength and subject motion present critical challenges that will have to be addressed to make camera-based pulse oximetry practically feasible.

Content Adaptive Coding Artifact Reduction for Decompressed Video and Images

Most artifact reduction techniques blur the details of the images while removing various coding artifacts. In this paper, we propose a novel and explicit approach for classifying blocks into detailed regions, intermediate regions and smooth regions. The classification is based on the information content of the underlying region, which is quantized by local entropy calculated on the PDF of the pixel intensity distribution. The entropy is used as an indicator of how much smoothing is needed for a certain region. Experimental results show that our proposed algorithm can preserve the details and reduce coding artifacts better than more expensive state of the art techniques.

Enhancement of compressed video signals using a local blockiness metric

This paper presents a new method for enhancement of the visual quality of compressed video sequences. The algorithm detects the location of a block grid, reduces coding artifacts and enhances sharpness of image details using integrated filtering that ensures low implementation cost and high quality. The results of our experiments show the high efficiency of the proposed approach.

Adaptive Repair of Compressed Video Signals using Local Objective Metrics of Blocking Artifacts

The paper presents a new objective metrics of blocking artifacts visibility in MPEG compressed video sequences. The metric estimates a local visibility of the block grid by analyzing the discontinuity of a pixel intensity trend across the block edge and by comparing it against pixel activities within blocks. Application of the local blockiness metrics for adaptive control of low-pass filtering provides significant reduction of coding artifacts without blurring of image details. The results of our experiments show the high efficiency of the proposed approach.

Motion-compensated techniques for enhancement of low-quality compressed videos

Algorithms for enhancement of low quality compressed videos are described and evaluated in this paper. Cascaded and combined spatio-temporal filters using hierarchical motion estimation and occlusion area detection are investigated for removal of severe coding artifacts and temporal flickering. Both objective and subjective evaluations prove that temporal filtering can significantly improve the video quality of low bit rate video sequences. The proposed methods could therefore be a differentiating feature for future IPTV design.