Ofer Hadar

Image resolution limits resulting from mechanical vibrations. Part IV: real-time numerical calculation of optical transfer functions and experimental verification

A method of calculating numerically the optical transfer function appropriate to any type of image motion and vibration, including random ones, has been developed. We compare the numerical calculation method to the experimental measurement; the close agreement justifies implementation in image restoration for blurring from any type of image motion. In addition, statistics regarding the limitation of resolution as a function of relative exposure time for low-frequency vibrations involving random blur are described. An analytical approximation to the probability density function for random blur has been obtained. This can be used for the determination of target acquisition probability. A comparison of image quality is presented for three different types of motion: linear, acceleration, and high-frequency vibration for the same blur radius. The parameter considered is the power spectrum of the picture.

Performance comparison of H.265/MPEG-HEVC, VP9, and H.264/MPEG-AVC encoders

This work presents a performance comparison of the two latest video coding standards H.264/MPEG-AVC and H.265/MPEG-HEVC (High-Efficiency Video Coding) as well as the recently published proprietary video coding scheme VP9. According to the experimental results, which were obtained for a whole test set of video sequences by using similar encoding configurations for all three examined representative encoders, H.265/MPEG-HEVC provides significant average bit-rate savings of 43.3% and 39.3% relative to VP9 and H.264/MPEG-AVC, respectively. As a particular aspect of the conducted experiments, it turned out that the VP9 encoder produces an average bit-rate overhead of 8.4% at the same objective quality, when compared to an open H.264/MPEG-AVC encoder implementation - the x264 encoder. On the other hand, the typical encoding times of the VP9 encoder are more than 100 times higher than those measured for the x264 encoder. When compared to the full-fledged H.265/MPEG-HEVC reference software encoder implementation, the VP9 encoding times are lower by a factor of 7.35, on average.

A Hybrid Compression Method for Integral Images Using Discrete Wavelet Transform and Discrete Cosine Transform

Integral imaging (II) is a promising three-dimensional (3-D) imaging technique that uses an array of diffractive or refractive optical elements to record the 3-D information on a conventional digital sensor. With II, the object information is recorded in the form of an array of subimages, each representing a slightly different perspective of the object In order to obtain high-quality 3-D images, digital sensors with a large number of pixels are required. Consequently, high-quality II involves recording and processing large amounts of data. In this paper, we present a compression method developed for the particular characteristics of the digitally recorded integral image. The compression algorithm is based on a hybrid technique implementing a four-dimensional transform combining the discrete wavelet transform and the discrete cosine transform. The proposed algorithm outperforms the baseline JPEG compression scheme applied to II and a previous compression method developed for II based on MPEG II.

Image resolution limits resulting from mechanical vibrations. Part III:numerical calculation of modulation transfer function

Low-frequency mechanical vibrations are a significant problem in robotics, machine vision, and practical reconnaissance where primary image vibrations involve random process blur radii. They cannot be described by an analytical MTF. A method of numerical calculation of MTF, relevant in principle to any type of image motion, is presented. It is demonstrated here for linear, high, and low vibration frequencies. The method yields the expected closed form solutions for linear and high-frequency motion. The low-vibration-frequency situation involves random process blur radii and MTFs that can only be handled statistically since no closed form solution is possible. This is illustrated here. Comparisons are made to a closed form approximate MTF solution suggested previously for low-frequency motion. Agreement between that analytical approximation and exact MTF calculated numerically is generally good, especially for relatively large and linear motion blur radius situations. For nonlinear short exposure motion, MTF levels off at relatively high nonzero values and never approaches zero. Such situations yield a two-fold benefit: (1) larger spatial frequency bandwidth and (2) higher MTF values at all spatial frequencies since MTF does not approach zero.

PCRTT Enhancement for Off-Line Video Smoothing

An enhancement of the Piecewise Constant Rate Transmission and Transport (PCRTT) algorithm for reducing the burstiness of a video stream, based on smoothing constant interval is proposed. The new algorithm, called e-PCRTT, relies on geometrical consideration rather than traditional rate-control analysis. E-PCRTT is shown to construct transmission rate-plans with smaller buffer sizes, as compared to the original PCRTT. Alternatively, for the same buffer size, e-PCRTT reduces the number of bandwidth changes as compared to PCRTT. In addition, e-PCRTT produces a rate-plan that requires a smaller initial playback delay.

Effects of an Encoding Scheme on Perceived Video Quality Transmitted Over Lossy Internet Protocol Networks

We analyze viewer-perceived quality of a compressed video stream, transmitted over a lossy IP network with a quality of service mechanism. The parameters of the encoding schemes include the transmission bit rate, the compression depth, the frame size and the frame rate. We demonstrate that when jointly considering the impact of the coding bit rate, the packet loss ratio and the video characteristics, we can identify an optimal encoding scheme that maximizes viewer-perceived quality. The video content, the compression and the transmission are represented by a vector X which contains d parameters. Based on subjective tests, we obtain a set of observation pairs of labeled samples Pi = {Xi, Qi} , where Qi is the quality class related to the vector of input parameters Xi. To determine the significance of these results, we use the analysis of variance (ANOVA) statistical method, which identifies those factors that cause differences in the averages in the subjective tests results, and determines the significance of the results. Finally, we introduce a novel method to predict an optimal encoding scheme based on canonical discriminant analysis (CDA) for feature classification.

Dynamic computational complexity and bit allocation for optimizing H.264/AVC video compression

In this work we present a novel approach for optimizing H.264/AVC video compression by dynamically allocating computational complexity (such as a number of CPU clocks) and bits for encoding each coding element (basic unit) within a video sequence, according to its predicted MAD (mean absolute difference). Our approach is based on a computational complexity-rate-distortion (C-R-D) analysis, which adds a complexity dimension to the conventional rate-distortion (R-D) analysis. Both theoretically and experimentally, we prove that by implementing the proposed approach better results are achieved. In addition, we present a method and system for implementing the proposed approach, and for controlling computational complexity and bit allocation in real-time and off-line video coding. For allocating a corresponding group of coding modes and the quantization step-size, we develop computational complexity - complexity step - rate (C-I-R) and rate - quantization step-size - computational complexity (R-Q-C) models.

ROI adaptive scalable video coding for limited bandwidth wireless networks

Much of the attention in the field of video adaptation has been directed to the Scalable Video Coding (SVC), which is the extension of the H.264/AVC standard, since the bit-stream scalability for video is a desirable feature for many multimedia applications. The need for the scalability mainly arises from the need for spatial formats, bit rates or power. To fulfill these requirements, it would be beneficial to simultaneously transmit or store video in variety of spatial/temporal resolutions and qualities, leading to the video bit-stream scalability. Regions-of-interest (ROI) coding is a desirable feature in future applications of Scalable Video Coding. For those SVC applications, users at the decoder side usually wish to receive a high-quality decoded video stream, containing the desired ROI, which should be adaptively selected from the pre-encoded scalable bit-stream. In this work, we present a novel ROI adaptive scalable video coding scheme, enabling to adaptively set desirable ROI location, size, resolution and bit-rate, according to the limited network bandwidth and predefined settings. This, in turn, will enable providing an effective rate control for multiple ROIs, thereby enabling adaptively selecting the required ROI from multiple ROIs in the scalable bit-stream, and adaptively changing ROI spatial resolution, ROI visual quality or amount of bits allocated for each ROI, according to the network bandwidth and users settings (i.e., users display resolution, etc.).

A metric for no-reference video quality assessment for HD TV delivery based on saliency maps

This paper contributes to objective video quality assessment of broadcasted HDTV content without reference. In this context we present a new No-Reference video quality metric taking into account the behavior of Human Visual System. This new metric called WMBER is based on macro-blocks error detection weighted by saliency maps computed at the decoder side. Moreover, both macro-block error detection and saliency maps processing require only partial decoding allowing real-time performance. A subjective experiment has been carried out to evaluate the performances of the proposed metric. The results are compared to the Full Reference metric MSE. The evaluation of the results shows that the proposed method provides a very good prediction of subjective measures.

Restoration of images degraded by extreme mechanical vibrations

A method of numerically calculating the optical transfer function appropriate to any type of image motion and vibration, including random, has been recently developed. This method has been verified experimentally with real vibrations, and the close agreement justifies implementation in image restoration from blur deriving from any type of image motion, including random displacement. Here, image restorations of actual physically degraded images are presented, based on a constrained least squares improvement of the original Wiener filter. Even for extreme vibrations where the blur extent is much larger than the blurred detail, restoration is quite complete. The key to restoration is the determination of the optical transfer function unique to the particular image motion and vibration causing the blur. Results are also presented for low vibration frequency motion of random blur extent, as well as for high vibration frequencies.