Layer Selection in Progressive Transmission of Motion-Compensated JPEG2000 Video

MCJ2K (Motion-Compensated JPEG2000) is a video codec based on MCTF (Motion- Compensated Temporal Filtering) and J2K (JPEG2000). MCTF analyzes a sequence of images, generating a collection of temporal sub-bands, which are compressed with J2K. The R/D (Rate-Distortion) performance in MCJ2K is better than the MJ2K (Motion JPEG2000) extension, especially if there is a high level of temporal redundancy. MCJ2K codestreams can be served by standard JPIP (J2K Interactive Protocol) servers, thanks to the use of only J2K standard file formats. In bandwidth-constrained scenarios, an important issue in MCJ2K is determining the amount of data of each temporal sub-band that must be transmitted to maximize the quality of the reconstructions at the client side. To solve this problem, we have proposed two rate-allocation algorithms which provide reconstructions that are progressive in quality. The first, OSLA (Optimized Sub-band Layers Allocation), determines the best progression of quality layers, but is computationally expensive. The second, ESLA (Estimated-Slope sub-band Layers Allocation), is sub-optimal in most cases, but much faster and more convenient for real-time streaming scenarios. An experimental comparison shows that even when a straightforward motion compensation scheme is used, the R/D performance of MCJ2K competitive is compared not only to MJ2K, but also with respect to other standard scalable video codecs

Scalable video/image transmission using rate compatible PUM turbo codes

The robust delivery of video over emerging wireless networks poses many challenges due to the heterogeneity of access networks, the variations in streaming devices, and the expected variations in network conditions caused by interference and coexistence. The proposed approach exploits the joint optimization of a wavelet-based scalable video/image coding framework and a forward error correction method based on PUM turbo codes. The scheme minimizes the reconstructed image/video distortion at the decoder subject to a constraint on the overall transmission bitrate budget. The minimization is achieved by exploiting the rate optimization technique and the statistics of the transmission channel

Optical network technologies for future digital cinema

Digital technology has transformed the information flow and support infrastructure for numerous application domains, such as cellular communications. Cinematography, traditionally, a film based medium, has embraced digital technology leading to innovative transformations in its work flow. Digital cinema supports transmission of high resolution content enabled by the latest advancements in optical communications and video compression. In this paper we provide a survey of the optical network technologies for supporting this bandwidth intensive traffic class. We also highlight the significance and benefits of the state of the art in optical technologies that support the digital cinema work flow

Mesh-based video coding for low bit-rate communications

In this paper, a new method for low bit-rate content-adaptive mesh-based video coding is proposed. Intra-frame coding of this method employs feature map extraction for node distribution at specific threshold levels to achieve higher density placement of initial nodes for regions that contain high frequency features and conversely sparse placement of initial nodes for smooth regions. Insignificant nodes are largely removed using a subsequent node elimination scheme. The Hilbert scan is then applied before quantization and entropy coding to reduce amount of transmitted information. For moving images, both node position and color parameters of only a subset of nodes may change from frame to frame. It is sufficient to transmit only these changed parameters. The proposed method is well-suited for video coding at very low bit rates, as processing results demonstrate that it provides good subjective and objective image quality at a lower number of required bits

Generative Compression

Traditional image and video compression algorithms rely on hand-crafted encoder/decoder pairs (codecs) that lack adaptability and are agnostic to the data being compressed. Here we describe the concept of generative compression, the compression of data using generative models, and suggest that it is a direction worth pursuing to produce more accurate and visually pleasing reconstructions at much deeper compression levels for both image and video data. We also demonstrate that generative compression is orders-of-magnitude more resilient to bit error rates (e.g. from noisy wireless channels) than traditional variable-length coding schemes

An efficient error resilience scheme based on wyner-ziv coding for region-of-Interest protection of wavelet based video transmission

In this paper, we propose a bandwidth efficient error resilience scheme for wavelet based video transmission over wireless channel by introducing an additional Wyner-Ziv (WZ) stream to protect region of interest (ROI) in a frame. In the proposed architecture, the main video stream is compressed by a generic wavelet domain coding structure and passed through the error prone channel without any protection. Meanwhile, the predefined ROI area related wavelet coefficients obtained after an integer wavelet transform will be specially protected by WZ codec in an additional channel during transmission. At the decoder side, the error-prone ROI related wavelet coefficients will be used as side information to help decoding the WZ stream. Different size of WZ bit streams can be applied in order to meet different bandwidth condition and different requirement of end users. The simulation results clearly revealed that the proposed scheme has distinct advantages in saving bandwidth comparing with fully applied FEC algorithm to whole video stream and in the meantime offer the robust transmission over error prone channel for certain video applications

On a region-of-interest based approach to robust wireless video transmission

This paper presents a scheme aiming at transmitting real-time video to wireless channel with vigorously varying quality, which is in practice the norm rather than the exception. Region of Interest (ROI) is an efficient approach to making the video more adaptive to the wireless channel because ROI is the region that human eyes tend to put more attention to than the Remainder Region (RM). In our proposed scheme, we will adopt this feature. The real-time source video stream is divided into two regions, the ROI and the RM regions. The two regions will be encoded using H.263 standard codec such that the video transmission is adaptive to the current channel state, which is characterized by the effective data rate that varies from tens of kilobits per second to hundreds of kilobits per second. Channel state parameters are fed back to the source coder to adjust the compression ratio as well as the intra/inter options of the encoders. Results including frame loss probability, compression characteristics, Peak Signal the Noise Ratio (PSNR) against channel states are given, indicating that the resulting adaptive video codec can respond judiciously to time-varying channel quality. Our scheme is evaluated together with a ROI-enabled moving picture coding standard JPEG2000. Using the features provided in JPEG2000, we have made the JPEG2000 codec adaptive to the vigorously varying wireless channel and then compared it with the H.263 scheme. Our technique is suitable for a broad area of applications including real-time news reporting and video conferencing.published_or_final_versio

RLFC: Random Access Light Field Compression using Key Views and Bounded Integer Encoding

We present a new hierarchical compression scheme for encoding light field images (LFI) that is suitable for interactive rendering. Our method (RLFC) exploits redundancies in the light field images by constructing a tree structure. The top level (root) of the tree captures the common high-level details across the LFI, and other levels (children) of the tree capture specific low-level details of the LFI. Our decompressing algorithm corresponds to tree traversal operations and gathers the values stored at different levels of the tree. Furthermore, we use bounded integer sequence encoding which provides random access and fast hardware decoding for compressing the blocks of children of the tree. We have evaluated our method for 4D two-plane parameterized light fields. The compression rates vary from 0.08 - 2.5 bits per pixel (bpp), resulting in compression ratios of around 200:1 to 20:1 for a PSNR quality of 40 to 50 dB. The decompression times for decoding the blocks of LFI are 1 - 3 microseconds per channel on an NVIDIA GTX-960 and we can render new views with a resolution of 512X512 at 200 fps. Our overall scheme is simple to implement and involves only bit manipulations and integer arithmetic operations.Comment: Accepted for publication at Symposium on Interactive 3D Graphics and Games (I3D '19

Dynamic Background Segmentation for Remote Reference Image Updating within Motion Detection JPEG2000

International audienceWe present in this paper a new system based on Motion JPEG2000 intended for road surveillance application. The system uses a reference image and consists in 4 processing steps, namely initialization phase where the first reference image is built, reference estimation, motion segmentation (foreground extraction, ROI mask), and JPEG2000 coding. A first order recursive filter is used to build a reference image that corresponds to the background image. The obtained background is sent to the decoder once for all. The reference image at the coder side is estimated according to a Gaussian mixture model. The remote reference image is updated when specific conditions are met. The updating remote reference is triggered according to the states of mobile objects in the scene (no, few or lot of mobiles). The motion detection given by classical background subtraction technique is performed in order to extract a binary mask. The motion mask gives the region of interest of the system. The JPEG2000 image coded with a ROI option is sent towards the decoder. The decoder receives, decodes the image and builds the implicit binary ROI mask. Then, the decoder builds the displayed image using the reference image, the current image and the mask