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Daala is a new royalty-free video codec based on perceptually-driven coding techniques. We explore using its keyframe format for still picture coding and show how it has improved over the past year. We believe the technology used in Daala could be the basis of an excellent, royalty-free image format.
Recently, an annihilating filter based low-rank Hankel matrix approach (ALOHA) was proposed as a general framework for sparsity-driven k-space interpolation method for compressed sensing MRI (CS-MRI). The principle of ALOHA framework is based on the fundamental duality between the transform domain sparsity in the primary space and the low-rankness of weighted Hankel matrix in Fourier domain, which...
Super Resolution (SR) addresses the problem of image and video upscaling. Most of the best performing SR methods do not take into account any compression prior into the degradation model. Consequently, compression artifacts can be undesirably amplified during SR. In the present work, we propose a novel HEVC-dedicated approach for embedding SR results into a domain that closely fits the compressed...
With the recent improvements in 3-D capture technologies for applications such as virtual reality, preserving cultural artifacts, and mobile mapping systems, new methods for compressing 3-D point cloud representations are needed to reduce the amount of bandwidth or storage consumed. For point clouds having attributes such as color associated with each point, several existing methods perform attribute...
We introduce the Gaussian Process Transform (GPT), an orthogonal transform for signals defined on a finite but otherwise arbitrary set of points in a Euclidean domain. The GPT is obtained as the Karhunen-Loéve Transform (KLT) of the marginalization of a Gaussian Process defined on the domain. Compared to the Graph Transform (GT), which is the KLT of a Gauss Markov Random Field over the same set of...
Conventionally, complex motion in video sequences is approximated by smaller block units in order to be representable by a translational motion model. This approximation results in a fine block partitioning and a high prediction error, both at cost of more data rate than potentially necessary. A worthwhile data reduction has been shown to be achievable by adding a higher order motion model to the...
The Karhunen-Loeve Transform (KLT) is a popular transform used in multiple image processing scenarios. Sometimes, the application of the KLT is not carried out as a single transform over an entire image. Rather, the image is divided into smaller spatial regions (segments), each of which is transformed by a smaller dimensional KLT. Such a situation may penalize the transform efficiency. An improvement...
We propose an algorithm that accomplishes transform-coded, spatiotemporal, pel-recursive video compression. Traditional pel-recursive coders obtain sophisticated spatio-temporal predictions for the current pixel based on previously decoded data. The resulting per-pixel prediction errors are encoded independently so that the decoder can use previously-encoded pixels in the prediction of the current...
The efficiency improvements achieved by new video coding standards come at the cost of a huge increase in the encoder computational complexity. Paradoxically, such increasing complexity is commonly addressed by methods that have an adverse effect on coding efficiency. In this work, we propose a method to reduce the complexity of HEVC Hadamard ME, without compromising coding efficiency. Our method...
Adaptive sparse representation has been heavily exploited in signal processing and computer vision. Recently, sparsifying transform learning received interest for its cheap computation and optimal updates in the alternating algorithms. In this work, we develop a methodology for learning a Flipping and Rotation Invariant Sparsifying Transform, dubbed FRIST, to better represent natural images that contain...
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