Subjective Quality Evaluation of H.264 High-Definition Video Coding versus Spatial Up-Scaling and Interlacing

International audienceThe upcoming High-De nition format for video display provides high-quality content, especially when displayed on adapted devices. When combined with video coding techniques such as MPEG-4 AVC/H.264, the transmission of High-De nition video content on broadcast networks becomes possible. Nonetheless, transmitting and decoding such video content is a real challenge. Therefore, intermediate formats based on lower frame resolutions or interlaced coding are still provided to address targets with limited resources. Using these formats, the nal video quality depends on the postprocessing tools employed at the receiver to upsample and de-interlace these streams. In this paper, we compare the full-HD format to three possible scenarios to generate a full-HD stream from intermediate formats. We present the results of subjective tests that compare the visual quality of each scenario when using the same bitrate. The results show that using the same bitrate, the videos generated from lower-resolution formats reach similar quality compared to the full-HD videos

Testing QoE in Different 3D HDTV Technologies

The three dimensional (3D) display technology has started flooding the consumer television market. There is a number of different systems available with different marketing strategies and different advertised advantages. The main goal of the experiment described in this paper is to compare the systems in terms of achievable Quality of Experience (QoE) in different situations. The display systems considered are the liquid crystal display using polarized light and passive lightweight glasses for the separation of the left- and right-eye images, a plasma display with time multiplexed images and active shutter glasses and a projection system with time multiplexed images and active shutter glasses. As no standardized test methodology has been defined for testing of stereoscopic systems, we develop our own approach to testing different aspects of QoE on different systems without reference using semantic differential scales. We present an analysis of scores with respect to different phenomena under study and define which of the tested aspects can really express a difference in the performance of the considered display technologies

Generalized motion and edge adaptive interpolation de-interlacing algorithm

This paper presents a generalized motion and edge adaptive de-interlacing framework, which offers a structured way to develop de-interlacing algorithm. The framework encompasses many typical de-interlacing algorithms, ranging from simple interpolation based algorithms, to more complex edge dependent and motion adaptive algorithms. Based on this framework, we develop a new de-interlacing algorithm which is efficient and artifacts-free. The proposed algorithm was evaluated by five video sequences, namely, "Akiyo", Mother and Daughter", "Silent", "Foreman" and "Stefan". Experimental results confirm that the proposed algorithm performs, both objectively and subjectively, much better than other similar algorithms. These promising results indicate that the proposed framework has good potential for realizing even better de-interlacing algorithms.postprin

Evaluation of the color image and video processing chain and visual quality management for consumer systems

With the advent of novel digital display technologies, color processing is increasingly becoming a key aspect in consumer video applications. Today’s state-of-the-art displays require sophisticated color and image reproduction techniques in order to achieve larger screen size, higher luminance and higher resolution than ever before. However, from color science perspective, there are clearly opportunities for improvement in the color reproduction capabilities of various emerging and conventional display technologies. This research seeks to identify potential areas for improvement in color processing in a video processing chain. As part of this research, various processes involved in a typical video processing chain in consumer video applications were reviewed. Several published color and contrast enhancement algorithms were evaluated, and a novel algorithm was developed to enhance color and contrast in images and videos in an effective and coordinated manner. Further, a psychophysical technique was developed and implemented for performing visual evaluation of color image and consumer video quality. Based on the performance analysis and visual experiments involving various algorithms, guidelines were proposed for the development of an effective color and contrast enhancement method for images and video applications. It is hoped that the knowledge gained from this research will help build a better understanding of color processing and color quality management methods in consumer video

Motion and edge adaptive interpolation de-interlacing algorithm

This paper presents a new motion and edge adaptive de-interlacing algorithm, which is efficient and artifacts-free. It is novel in the sense that it introduces a way to properly interpolate the two (odd and even) field images according to the information provided by the simplest form of motion detection and edge orientation estimation methods. The proposed algorithm was evaluated by three video sequences, namely, 'Akiyo', 'Silent', 'Foreman'. Experimental results confirm that the proposed algorithm performs, both objectively and subjectively, much better than other similar algorithms. These promising results indicate that the proposed interpolation approach has good potential to realize even better de-interlacing algorithms, if more sophisticated motion detection and edge orientation estimation methods are employed.postprintThe 10th WSEAS international conference on Computers (ICCOMP'06), Athens, Greece, 13-15 July 2006. In Proceedings of ICCOMP, 2006, p. 1030-103

Motion and edge adaptive interpolation de-interlacing algorithm

This paper presents a new motion and edge adaptive de-interlacing algorithm, which is efficient and artifacts-free. It is novel in the sense that it introduces a way to properly interpolate the two (odd and even) field images according to the information provided by the simplest form of motion detection and edge orientation estimation methods. The proposed algorithm was evaluated by three video sequences, namely, 'Akiyo', 'Silent', 'Foreman'. Experimental results confirm that the proposed algorithm performs, both objectively and subjectively, much better than other similar algorithms. These promising results indicate that the proposed interpolation approach has good potential to realize even better de-interlacing algorithms, if more sophisticated motion detection and edge orientation estimation methods are employed.postprintThe 10th WSEAS international conference on Computers (ICCOMP'06), Athens, Greece, 13-15 July 2006. In Proceedings of ICCOMP, 2006, p. 1030-103

Adaptive deinterlacing of video sequences using motion data

In this work an efficient motion adaptive deinterlacing method with considerable improvement in picture quality is proposed. A temporal deinterlacing method has a high performance in static images while a spatial method has a better performance in dynamic parts. In the proposed deinterlacing method, a motion adaptive interpolator combines the results of a spatial method and a temporal method based on motion activity level of video sequence. A high performance and low complexity algorithm for motion detection is introduced. This algorithm uses five consecutive interlaced video fields for motion detection. It is able to capture a wide range of motions from slow to fast. The algorithm benefits from a hierarchal structure. It starts with detecting motion in large partitions of a given field. Depending on the detected motion activity level for that partition, the motion detection algorithm might recursively be applied to sub-blocks of the original partition. Two different low pass filters are used during the motion detection to increase the algorithm accuracy. The result of motion detection is then used in the proposed motion adaptive interpolator. The performance of the proposed deinterlacing algorithm is compared to previous methods in the literature. Experimenting with several standard video sequences, the method proposed in this work shows excellent results for motion detection and deinterlacing performance

Colonoscopy Image Pre-Processing for the Development of Computer-Aided Diagnostic Tools

Colorrectal cancer is the third most frequently diagnosed cancer worldwide. The American Cancer Society estimates that there will be almost 100,000 new patients diagnosed with colorectal cancer and that around 50,000 people will die as a consequence of this in 2016. The increase of life expectancy and the increment of the number of diagnostic tests conducted have had a great impact on the amount of cancers being detected. Among other diagnostic tools, colonoscopy is the most prevalent. In order to help endoscopists cope with the increasing amount of tests that have to be carried out, there exists a need to develop automated tools that aid diagnosis. The characteristics of the colon make pre-processing essential to eliminate artefacts that degrade the quality of exploratory images. The goal of this chapter is to describe the most common issues of colonoscopic imagery as well the existing methods for their optimal detection and correction