1,928 research outputs found
JPEG steganography with particle swarm optimization accelerated by AVX
Digital steganography aims at hiding secret messages in digital data transmitted over insecure channels. The JPEG format is prevalent in digital communication, and images are often used as cover objects in digital steganography. Optimization methods can improve the properties of images with embedded secret but introduce additional computational complexity to their processing. AVX instructions available in modern CPUs are, in this work, used to accelerate data parallel operations that are part of image steganography with advanced optimizations.Web of Science328art. no. e544
Digital Video Concepts, Methods, and Metrics: Quality, Compression, Performance, and Power Trade-off Analysis
Digital Video Concepts, Methods, and Metrics: Quality, Compression, Performance, and Power Trade-off Analysis is a concise reference for professionals in a wide range of applications and vocations. It focuses on giving the reader mastery over the concepts, methods and metrics of digital video coding, so that readers have sufficient understanding to choose and tune coding parameters for optimum results that would suit their particular needs for quality, compression, speed and power. The practical aspects are many: Uploading video to the Internet is only the beginning of a trend where a consumer controls video quality and speed by trading off various other factors. Open source and proprietary applications such as video e-mail, private party content generation, editing and archiving, and cloud asset management would give further control to the end-user. Digital video is frequently compressed and coded for easier storage and transmission. This process involves visual quality loss due to typical data compression techniques and requires use of high performance computing systems. A careful balance between the amount of compression, the visual quality loss and the coding speed is necessary to keep the total system cost down, while delivering a good user experience for various video applications. At the same time, power consumption optimizations are also essential to get the job done on inexpensive consumer platforms. Trade-offs can be made among these factors, and relevant considerations are particularly important in resource-constrained low power devices. To better understand the trade-offs this book discusses a comprehensive set of engineering principles, strategies, methods and metrics. It also exposes readers to approaches on how to differentiate and rank video coding solutions
ICNet for Real-Time Semantic Segmentation on High-Resolution Images
We focus on the challenging task of real-time semantic segmentation in this
paper. It finds many practical applications and yet is with fundamental
difficulty of reducing a large portion of computation for pixel-wise label
inference. We propose an image cascade network (ICNet) that incorporates
multi-resolution branches under proper label guidance to address this
challenge. We provide in-depth analysis of our framework and introduce the
cascade feature fusion unit to quickly achieve high-quality segmentation. Our
system yields real-time inference on a single GPU card with decent quality
results evaluated on challenging datasets like Cityscapes, CamVid and
COCO-Stuff.Comment: ECCV 201
Accelerating BPC-PaCo through visually lossless techniques
Fast image codecs are a current need in applications that deal with large amounts of images. Graphics Processing Units (GPUs) are suitable processors to speed up most kinds of algorithms, especially when they allow fine-grain parallelism. Bitplane Coding with Parallel Coefficient processing (BPC-PaCo) is a recently proposed algorithm for the core stage of wavelet-based image codecs tailored for the highly parallel architectures of GPUs. This algorithm provides complexity scalability to allow faster execution at the expense of coding efficiency. Its main drawback is that the speedup and loss in image quality is controlled only roughly, resulting in visible distortion at low and medium rates. This paper addresses this issue by integrating techniques of visually lossless coding into BPC-PaCo. The resulting method minimizes the visual distortion introduced in the compressed file, obtaining higher-quality images to a human observer. Experimental results also indicate 12% speedups with respect to BPC-PaCo
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