Model of zonular forces on the lens capsule during accommodation.

How the human eye focuses for near; i.e. accommodates, is still being evaluated after more than 165 years. The mechanism of accommodation is essential for understanding the etiology and potential treatments for myopia, glaucoma and presbyopia. Presbyopia affects 100% of the population in the fifth decade of life. The lens is encased in a semi-elastic capsule with attached ligaments called zonules that mediate ciliary muscle forces to alter lens shape. The zonules are attached at the lens capsule equator. The fundamental issue is whether during accommodation all the zonules relax causing the central and peripheral lens surfaces to steepen, or the equatorial zonules are under increased tension while the anterior and posterior zonules relax causing the lens surface to peripherally flatten and centrally steepen while maintaining lens stability. Here we show with a balloon capsule zonular force model that increased equatorial zonular tension with relaxation of the anterior and posterior zonules replicates the topographical changes observed during in vivo rhesus and human accommodation of the lens capsule without lens stroma. The zonular forces required to simulate lens capsule configuration during in vivo accommodation are inconsistent with the general belief that all the zonules relax during accommodation.

Finite element analysis of zonular forces.

To determine the effect of zonular forces on lens capsule topography, a finite element (FE) analyses of lens capsules with no lens stroma and constant and variable thickness with anterior capsulotomies of 1.5 mm-6.5 mm were evaluated when subjected to equatorial (Ez), anterior (Az) and posterior (Pz) zonular forces. The lens capsule was considered in the unaccommodated state when the total initial zonular force was 0.00075 N or 0.3 N. From the total 0.00075 N zonular force, the Ez force was increased in 0.000125 N steps for a maximum force of 0.03 N and simultaneously the Az plus Pz force was reduced in 0.000125 N steps to zero. In addition, the force of all the zonules was reduced from 0.00075 N and separately from 0.3 N in 0.000125 N steps to zero. Only when Ez force was increased as Az and Pz force was reduced did the capsule topography simulate in vivo observations with the posterior capsule pole bowing posteriorly. The posterior bowing was directly related to Ez force and capsulotomy size. Whether the total force of all the zonules in the unaccommodated state was 0.00075 N or 0.3 N and reduced in steps to zero, the lens capsule topography did not emulate the in vivo observations. The FE analysis demonstrated that Ez tension increases while the Az and Pz tension decreases and that all the zonules do not relax during ciliary muscle contraction.

Can rubrics combat gender bias in faculty hiring?

Some bias persiste d, but rubric use should be encouraged.

Learning-Based Rate Control for Video-Based Point Cloud Compression.

Due to limited transmission resources and storage capacity, efficient rate control is important in Video-based Point Cloud Compression (V-PCC). In this paper, we propose a learning-based rate control method to improve the rate-distortion (RD) performance of V-PCC. A low-latency synchronous rate control structure is designed to reduce the overhead of pre-coding. The basic unit (BU) parameters are predicted accurately based on our proposed CNN-LSTM neural network, instead of the online updating approach, which can be inaccurate due to low consistency between adjacent 2D frames in V-PCC. When determining the quantization parameters for the BU, a patch-based clipping method is proposed to avoid unnecessary clipping. This approach is able to improve the RD performance and subjective dynamic point cloud quality. Experiments show that our proposed rate control method outperforms present approaches.

Low-Complexity Error Resilient HEVC Video Coding: A Deep Learning Approach.

Intra/inter switching-based error resilient video coding effectively enhances the robustness of video streaming when transmitting over error-prone networks. But it has a high computation complexity, due to the detailed end-to-end distortion prediction and brute-force search for rate-distortion optimization. In this article, a Low Complexity Mode Switching based Error Resilient Encoding (LC-MSERE) method is proposed to reduce the complexity of the encoder through a deep learning approach. By designing and training multi-scale information fusion-based convolutional neural networks (CNN), intra and inter mode coding unit (CU) partitions can be predicted by the networks rapidly and accurately, instead of using brute-force search and a large number of end-to-end distortion estimations. In the intra CU partition prediction, we propose a spatial multi-scale information fusion based CNN (SMIF-Intra). In this network a shortcut convolution architecture is designed to learn the multi-scale and multi-grained image information, which is correlated with the CU partition. In the inter CU partition, we propose a spatial-temporal multi-scale information fusion-based CNN (STMIF-Inter), in which a two-stream convolution architecture is designed to learn the spatial-temporal image texture and the distortion propagation among frames. With information from the image, and coding and transmission parameters, the networks are able to accurately predict CU partitions for both intra and inter coding tree units (CTUs). Experiments show that our approach significantly reduces computation time for error resilient video encoding with acceptable quality decrement.

Luminance Enhancement and Detail Preservation of Images and Videos Adapted to Ambient Illumination.

When images and videos are displayed on a mobile device in bright ambient illumination, fewer details can be perceived than in the dark. The detail loss in dark areas of the images/videos is usually more severe. The reflected ambient light and the reduced sensitivity of viewer's eyes are the major factors. We propose two tone mapping operators to enhance the contrast and details in images/videos. One is content independent and thus can be applied to any image/video for the given device and the given ambient illumination. The other tone mapping operator uses simple statistics of the content. Display contrast and human visual adaptation are considered to construct the tone mapping operators. Both operators can be solved efficiently. Subjective tests and objective measurement show the improved quality achieved by the proposed methods.

Generalization of the Dark Channel Prior for Single Image Restoration.

Images degraded by light scattering and absorption, such as hazy, sandstorm, and underwater images, often suffer color distortion and low contrast because of light traveling through turbid media. In order to enhance and restore such images, we first estimate ambient light using the depth-dependent color change. Then, via calculating the difference between the observed intensity and the ambient light, which we call the scene ambient light differential, scene transmission can be estimated. Additionally, adaptive color correction is incorporated into the image formation model (IFM) for removing color casts while restoring contrast. Experimental results on various degraded images demonstrate the new method outperforms other IFM-based methods subjectively and objectively. Our approach can be interpreted as a generalization of the common dark channel prior (DCP) approach to image restoration, and our method reduces to several DCP variants for different special cases of ambient lighting and turbid medium conditions.

Underwater Image Restoration Based on Image Blurriness and Light Absorption.

Underwater images often suffer from color distortion and low contrast, because light is scattered and absorbed when traveling through water. Such images with different color tones can be shot in various lighting conditions, making restoration and enhancement difficult. We propose a depth estimation method for underwater scenes based on image blurriness and light absorption, which can be used in the image formation model (IFM) to restore and enhance underwater images. Previous IFM-based image restoration methods estimate scene depth based on the dark channel prior or the maximum intensity prior. These are frequently invalidated by the lighting conditions in underwater images, leading to poor restoration results. The proposed method estimates underwater scene depth more accurately. Experimental results on restoring real and synthesized underwater images demonstrate that the proposed method outperforms other IFM-based underwater image restoration methods.

Tracking epithelial cell junctions in C. elegans embryogenesis with active contours guided by SIFT flow.

Quantitative analysis of cell shape in live samples is an important goal in developmental biology. Automated or semi-automated segmentation and tracking of cell nuclei has been successfully implemented in several biological systems. Segmentation and tracking of cell surfaces has been more challenging. Here, we present a new approach to tracking cell junctions in the developing epidermis of C. elegans embryos. Epithelial junctions as visualized with DLG-1::GFP form lines at the subapical circumference of differentiated epidermal cells and delineate changes in epidermal cell shape and position. We develop and compare two approaches for junction segmentation. For the first method (projection approach), 3-D cell boundaries are projected into 2D for segmentation using active contours with a nonintersecting force, and subsequently tracked using scale-invariant feature transform (SIFT) flow. The resulting 2-D tracked boundaries are then back-projected into 3-D space. The second method (volumetric approach) uses a 3-D extended version of active contours guided by SIFT flow in 3-D space. In both methods, cell junctions are manually located at the first time point and tracked in a fully automated way for the remainder of the video. Using these methods, we have generated the first quantitative description of ventral epidermal cell movements and shape changes during epidermal enclosure.

Syndecan defines precise spindle orientation by modulating Wnt signaling in C. elegans.

Wnt signals orient mitotic spindles in development, but it remains unclear how Wnt signaling is spatially controlled to achieve precise spindle orientation. Here, we show that C. elegans syndecan (SDN-1) is required for precise orientation of a mitotic spindle in response to a Wnt cue. We find that SDN-1 is the predominant heparan sulfate (HS) proteoglycan in the early C. elegans embryo, and that loss of HS biosynthesis or of the SDN-1 core protein results in misorientation of the spindle of the ABar blastomere. The ABar and EMS spindles both reorient in response to Wnt signals, but only ABar spindle reorientation is dependent on a new cell contact and on HS and SDN-1. SDN-1 transiently accumulates on the ABar surface as it contacts C, and is required for local concentration of Dishevelled (MIG-5) in the ABar cortex adjacent to C. These findings establish a new role for syndecan in Wnt-dependent spindle orientation.

Double-layer video transmission over decode-and-forward wireless relay networks using hierarchical modulation.

We consider a wireless relay network with a single source, a single destination, and a multiple relay. The relays are half-duplex and use the decode-and-forward protocol. The transmit source is a layered video bitstream, which can be partitioned into two layers, a base layer (BL) and an enhancement layer (EL), where the BL is more important than the EL in terms of the source distortion. The source broadcasts both layers to the relays and the destination using hierarchical 16-QAM. Each relay detects and transmits successfully decoded layers to the destination using either hierarchical 16-QAM or QPSK. The destination can thus receive multiple signals, each of which can include either only the BL or both the BL and the EL. We derive the optimal linear combining method at the destination, where the uncoded bit error rate is minimized. We also present a suboptimal combining method with a closed-form solution, which performs very close to the optimal. We use the proposed double-layer transmission scheme with our combining methods for transmitting layered video bitstreams. Numerical results show that the double-layer scheme can gain 2-2.5 dB in channel signal-to-noise ratio or 5-7 dB in video peak signal-to-noise ratio, compared with the classical single-layer scheme using conventional modulation.

Generalized unequal error protection LT codes for progressive data transmission.

The original design of standard digital fountain codes assumes that the coded information symbols are equally important. In many applications, some source symbols are more important than others, and they must be recovered prior to the rest. Unequal Error Protection (UEP) designs are attractive solutions for such source transmissions. In this study, we introduce a more generalized design for the first universal fountain code design, LT codes, that makes it particularly suited for progressive bit stream transmissions. We apply the generalized LT codes to a progressive source and show that it has better UEP properties than other published results in the literature. For example, using the proposed generalization, we obtained up to 1.7dB PSNR gain in a progressive image transmission scenario over the two major UEP fountain code designs.

Network-based H.264/AVC whole frame loss visibility model and frame dropping methods.

We examine the visual effect of whole frame loss by different decoders. Whole frame losses are introduced in H.264/AVC compressed videos which are then decoded by two different decoders with different common concealment effects: frame copy and frame interpolation. The videos are seen by human observers who respond to each glitch they spot. We found that about 39% of whole frame losses of B frames are not observed by any of the subjects, and over 58% of the B frame losses are observed by 20% or fewer of the subjects. Using simple predictive features which can be calculated inside a network node with no access to the original video and no pixel level reconstruction of the frame, we developed models which can predict the visibility of whole B frame losses. The models are then used in a router to predict the visual impact of a frame loss and perform intelligent frame dropping to relieve network congestion. Dropping frames based on their visual scores proves superior to random dropping of B frames.

Iterative channel decoding of FEC-based multiple-description codes.

Multiple description coding has been receiving attention as a robust transmission framework for multimedia services. This paper studies the iterative decoding of FEC-based multiple description codes. The proposed decoding algorithms take advantage of the error detection capability of Reed-Solomon (RS) erasure codes. The information of correctly decoded RS codewords is exploited to enhance the error correction capability of the Viterbi algorithm at the next iteration of decoding. In the proposed algorithm, an intradescription interleaver is synergistically combined with the iterative decoder. The interleaver does not affect the performance of noniterative decoding but greatly enhances the performance when the system is iteratively decoded. We also address the optimal allocation of RS parity symbols for unequal error protection. For the optimal allocation in iterative decoding, we derive mathematical equations from which the probability distributions of description erasures can be generated in a simple way. The performance of the algorithm is evaluated over an orthogonal frequency-division multiplexing system. The results show that the performance of the multiple description codes is significantly enhanced.

Concatenated block codes for unequal error protection of embedded bit streams.

A state-of-the-art progressive source encoder is combined with a concatenated block coding mechanism to produce a robust source transmission system for embedded bit streams. The proposed scheme efficiently trades off the available total bit budget between information bits and parity bits through efficient information block size adjustment, concatenated block coding, and random block interleavers. The objective is to create embedded codewords such that, for a particular information block, the necessary protection is obtained via multiple channel encodings, contrary to the conventional methods that use a single code rate per information block. This way, a more flexible protection scheme is obtained. The information block size and concatenated coding rates are judiciously chosen to maximize system performance, subject to a total bit budget. The set of codes is usually created by puncturing a low-rate mother code so that a single encoder-decoder pair is used. The proposed scheme is shown to effectively enlarge this code set by providing more protection levels than is possible using the code rate set directly. At the expense of complexity, average system performance is shown to be significantly better than that of several known comparison systems, particularly at higher channel bit error rates.

Wyner-Ziv video coding with classified correlation noise estimation and key frame coding mode selection.

We improve the overall rate-distortion performance of distributed video coding by efficient techniques of correlation noise estimation and key frame encoding. In existing transform-domain Wyner-Ziv video coding methods, blocks within a frame are treated uniformly to estimate the correlation noise even though the success of generating side information is different for each block. We propose a method to estimate the correlation noise by differentiating blocks within a frame based on the accuracy of the side information. Simulation results show up to 2 dB improvement over conventional methods without increasing encoder complexity. Also, in traditional Wyner-Ziv video coding, the intercorrelation of key frames is not exploited since they are simply intracoded. In this paper, we propose a frequency band coding mode selection for key frames to exploit similarities between adjacent key frames at the decoder. Simulation results show significant improvement especially for low-motion and high frame rate sequences. Furthermore, the advantage of applying both schemes in a hierarchical order is investigated. This method achieves additional improvement.

Performance analysis of n-channel symmetric FEC-based multiple description coding for OFDM networks.

Recently, multiple description source coding has emerged as an attractive framework for robust multimedia transmission over packet erasure channels. In this paper, we mathematically analyze the performance of n-channel symmetric FEC-based multiple description coding for a progressive mode of transmission over orthogonal frequency division multiplexing (OFDM) networks in a frequency-selective slowly-varying Rayleigh faded environment. We derive the expressions for the bounds of the throughput and distortion performance of the system in an explicit closed form, whereas the exact performance is given by an expression in the form of a single integration. Based on this analysis, the performance of the system can be numerically evaluated. Our results show that at high SNR, the multiple description encoder does not need to fine-tune the optimization parameters of the system due to the correlated nature of the subcarriers. It is also shown that, despite the bursty nature of the errors in a slow fading environment, FEC-based multiple description coding without temporal coding provides a greater advantage for smaller description sizes.

A versatile model for packet loss visibility and its application to packet prioritization.

In this paper, we propose a generalized linear model for video packet loss visibility that is applicable to different group-of-picture structures. We develop the model using three subjective experiment data sets that span various encoding standards (H.264 and MPEG-2), group-of-picture structures, and decoder error concealment choices. We consider factors not only within a packet, but also in its vicinity, to account for possible temporal and spatial masking effects. We discover that the factors of scene cuts, camera motion, and reference distance are highly significant to the packet loss visibility. We apply our visibility model to packet prioritization for a video stream; when the network gets congested at an intermediate router, the router is able to decide which packets to drop such that visual quality of the video is minimally impacted. To show the effectiveness of our visibility model and its corresponding packet prioritization method, experiments are done to compare our perceptual-quality-based packet prioritization approach with existing Drop-Tail and Hint-Track-inspired cumulative-MSE-based prioritization methods. The result shows that our prioritization method produces videos of higher perceptual quality for different network conditions and group-of-picture structures. Our model was developed using data from high encoding-rate videos, and designed for high-quality video transported over a mostly reliable network; however, the experiments show the model is applicable to different encoding rates.

Delay constrained multiplexing of video streams using dual-frame video coding.

We consider the multiplexing problem of transmitting multiple video source streams from a server over a shared channel. We use dual-frame video coding with high-quality Long-Term Reference (LTR) frames and propose multiplexing methods to reduce the sum of mean squared error for all the video streams. This paper makes several improvements to dual-frame video coding. A simple motion activity detection algorithm is used to choose the location of LTR frames as well as the number of bits given to such frames. An adaptive buffer-constrained rate-control algorithm is devised to accommodate the extra bits of the high-quality LTR frames. Multiplexing of video streams is studied under the constraint of a video encoder delay buffer. Using H.264/AVC, the results show considerable improvement over baseline schemes such as H.264 rate control when the video streams are encoded individually and over multiplexing methods proposed previously in the literature. The high-quality LTR frames are offset in time among different video streams. This provides the benefits of dual-frame coding with high-quality LTR frames while still fitting under the constraint of an output delay buffer.

Competitive equilibrium bitrate allocation for multiple video streams.

We consider the problem of simultaneous bitrate allocation for multiple video streams. Current methods for multiplexing video streams often rely on identifying the relative complexity of the video streams to improve the combined overall quality. In such methods, not all the videos benefit from the multiplexing process. Typically, the quality of high motion videos is improved at the expense of a reduction in the quality of low motion videos. In our approach, we use a competitive equilibrium allocation of bitrate to improve the quality of all the video streams by finding trades between videos across time. A central controller collects rate-distortion information from each video user and makes a joint bitrate allocation decision. Each user encodes and transmits his video at the allocated bitrate through a shared channel. The proposed method uses information about not only the differing complexity of the video streams at every moment but also the differing complexity of each stream over time. Using the competitive equilibrium bitrate allocation approach for multiple video streams, simulation results show that all the video streams perform better or at least as well as with individual encoding. The results of this research will be useful both for ad hoc networks that employ a cluster head model and for cellular architectures.