At present, massive amounts of image data have been generated at the power construction site. Due to the limitation of power communication transmission bandwidth, it is necessary to improve the low bit rate, high comp...
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ISBN:
(纸本)9781665423144
At present, massive amounts of image data have been generated at the power construction site. Due to the limitation of power communication transmission bandwidth, it is necessary to improve the low bit rate, high compression ratio, and anti-interference of the image, which is very necessary for on-site management personnel under the premise of ensuring efficient information transmission. Aiming at the above problems, this paper proposes an improved algorithm based on Set Partitioning in Hierarchical Trees (SPIHT). Firstly, the feature value of the image is extracted, and then the wavelet encoding is performed to obtain the compressed image. Compared with the traditional multi-level tree ensemble splitting algorithm, experimental data show that the image compressed by this algorithm has better visual effects and higher peak signal-to-noise ratio. Therefore, the method can effectively improve the transmission performance of the on-site image of the infrastructure construction, and ultimately improve the efficiency of the on-site inspection for violations.
In this paper, we propose a new approach for imagecompression based on compressive sensing (CS). We introduce a new formulation of sparse vectors for rearranging multilevel 2-D Wavelet coefficients into a structured ...
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ISBN:
(纸本)9781479986385
In this paper, we propose a new approach for imagecompression based on compressive sensing (CS). We introduce a new formulation of sparse vectors for rearranging multilevel 2-D Wavelet coefficients into a structured manner using parent-child relationships. We then use a Gaussian measurement matrix normalized with the weighted average Root Mean Squared (RMS) energies of different wavelet subbands. Compressed sampling is finally performed using this normalized measurement matrix. At the decoding stage, the image is reconstructed using a simple l_1-minimization technique. The proposed wavelet-based CS compression results in performance increase compared to other conventional CS-based techniques. Our experimental results show that the proposed algorithm outperforms existing approaches over different natural images.
JPEG 2000 is a new image coding system that uses state-of-the-art compression techniques based on wavelet technology. As interactive multimedia technologies evolve, the requirements for the file format used to store t...
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ISBN:
(纸本)9783037859353
JPEG 2000 is a new image coding system that uses state-of-the-art compression techniques based on wavelet technology. As interactive multimedia technologies evolve, the requirements for the file format used to store the image data continue to evolve. The size and bit depth collected for an image to increase the resolution and extend the dynamic range and color gamut. Discrete Wavelet transform based embedded image coding method is the basis of JPEG2000. image compression algorithm for the proper use and display of the image is a requirement for digital photography.
Huge SDRAM memory access bandwidth is the performance bottleneck for high definition video coding. Lossless imagecompression is efficient method to solve this problem. image pixels are compressed before writing into ...
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ISBN:
(纸本)9781479938827
Huge SDRAM memory access bandwidth is the performance bottleneck for high definition video coding. Lossless imagecompression is efficient method to solve this problem. image pixels are compressed before writing into SDRAM and decompressed after reading out from SDRAM. This work proposes a hardware-oriented lossless image compression algorithm, supporting block and line random access patterns flexibly.
In the era of intelligent media, we all need high quality image or video information. However, due to the limitation of bandwidth or storage resource, we usually use low bit rate coding technology for image compressio...
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ISBN:
(纸本)9781728123264
In the era of intelligent media, we all need high quality image or video information. However, due to the limitation of bandwidth or storage resource, we usually use low bit rate coding technology for imagecompression. But the image distortion caused will bring in a visually inferior experience, and the actual information obtained is often not sufficient. Therefore, the super-resolution reconstructed image coding technology is researched to provide a higher dynamic bit rate variation range. Based on image super-resolution reconstruction, this paper proposes two targeted imagecompression coding frameworks. Firstly, we compress the DCT down-sampled image as the input of super-resolution reconstruction, and use image completion as the pretreatment process of image super-resolution reconstruction, which effectively improves the quality of reconstructed image at low bit rate and, hence improves the coding efficiency. Secondly, a new imagecompression technique is proposed here which is based on residual compensation and super-resolution reconstruction. In the encoder, the super-resolution reconstructed image is subtracted from the original image to obtain the residual image which is compressed. In the decoder, the residual image is decompressed and added to the reconstructed image to complete the decoding process which achieves flexible rate control.
Traffic congestion has always been a major problem in the Philippines. This project study developed an integrated sensor system for intelligent transportation, which addressed the lack of automatic traffic monitoring ...
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ISBN:
(纸本)9781665485296
Traffic congestion has always been a major problem in the Philippines. This project study developed an integrated sensor system for intelligent transportation, which addressed the lack of automatic traffic monitoring systems to achieve traffic efficiency and safety. The researchers utilized different sensors in gathering data such as water level, temperature, and humidity within a certain area as well as a camera in capturing images and compared the three image compression algorithms, mainly the DCT (Discrete Cosine Transform), DWT (Discrete Wavelet Transform) and SVD (singular value decomposition) in terms of different parameters used in describing and identifying the best type of imagecompression to be applied prior to transmission to other different nodes. MSE (mean squared error) value, PSNR (Peak signal-to-noise ratio), Compress Ratio, and Process Time were the values of comparison in determining the best compression technique or algorithm for the gathered images. As a result, it was found that DCT characterized the best parameters for imagecompression. DCT produced the highest PSNR (52.41979dB), the lowest value for MSE (0.37247), and the lowest process time (0.16181s), while SVD was able to produce the most compressed image. This project also utilized solar renewable energy for the power management system, which enabled the system to run independently without any other external power source. This will be beneficial for the community to identify which roads can be used to optimize the mobility of the vehicles and maximize the use of renewable energy;hence will help reduce the traffic congestion issues in the country.
JPEG 2000 is a new image coding system that uses state-of-the-art compression techniques based on wavelet technology. As interactive multimedia technologies evolve, the requirements for the file format used to store t...
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JPEG 2000 is a new image coding system that uses state-of-the-art compression techniques based on wavelet technology. As interactive multimedia technologies evolve, the requirements for the file format used to store the image data continue to evolve. The size and bit depth collected for an image to increase the resolution and extend the dynamic range and color gamut. Discrete Wavelet transform based embedded image coding method is the basis of JPEG2000. image compression algorithm for the proper use and display of the image is a requirement for digital photography.
To provide a fast compressionalgorithm for high-resolution medical image sequences, an efficient three-dimensional (3D) separate descendant-based (SBD) set partitioning in hierarchical trees (SPIHT) algorithm (3D SDB...
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To provide a fast compressionalgorithm for high-resolution medical image sequences, an efficient three-dimensional (3D) separate descendant-based (SBD) set partitioning in hierarchical trees (SPIHT) algorithm (3D SDB-SPIHT) is proposed in this study. To accelerate the transformation, 3D integer wavelet transform is used first. Based on an efficient spatial-temporal tree structure, which is designed for the transformed coefficients, the authors propose a fast coding scheme by separating the descendant set into offspring set and leaves set. The proposed algorithm has more selectivity in deciding the scanning and coding of the descendant sets and hence the coding time is accelerated. Experimental results demonstrate that 3D SDB-SPIHT compresses medical images faster compared with traditional 3D SPIHT and other variations of 3D SPIHT.
imagecompression standards rely on predic coding. transform coding, quantization and entropy coding, in order to achieve high compression performance. Very recently, deep generative models have been used to optimize ...
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ISBN:
(纸本)9781538660706
imagecompression standards rely on predic coding. transform coding, quantization and entropy coding, in order to achieve high compression performance. Very recently, deep generative models have been used to optimize or replace some of these operations, with very promising results. However. so far no systematic and independent study of the coding performance of these algorithms has been carried out. In this paper, for the first time, we conduct a subjective evaluation of two recent deep learning-based imagecompression algorithnts, comparing them to JPEG 2000 and to the recent BPG image codec based on HEVC Intra. We found that compression approaches based on deep auto -encoders can achieve coding performance higher than JPEG 2000, and sometimes as good as BPG. We also show experimentally that the PSNR metric to be avoided when evaluating the visual quality of deep -learning-based methods, as artifacts have different characteristics from those of DCT or wavelet -based codecs. In particular, images compressed at low biirate appear more natural than JPEG 2000 coded pictu according to a no -reference naturalness measure. Our study indicates that deep generative models are likely to bring huge innovation into the video coding arena in the coming years.
Huge numbers of images are produced today with advent of the 'big data' era. To store and transmit data traditional compression methods are no longer satisfying. In this paper, we face this challenge and to ac...
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ISBN:
(纸本)9781509047970
Huge numbers of images are produced today with advent of the 'big data' era. To store and transmit data traditional compression methods are no longer satisfying. In this paper, we face this challenge and to achieve a higher compression rate we are taking the advantage of the correlations existing between images. An imagecompression system that encodes each image by referencing its correlated images in the cloud. By comparing these features, we first extract features from an image and retrieve its similar image from the massive images in the cloud. Different methods of compressing point cloud data such as directly by converting it into 2D images or by using tree- based approaches have been explored from the previous studies. In this study, rather than compress point cloud data directly to compress the image in cloud data, by converting it lossless into range images, and then using various image compression algorithms to reduce the volume of the data.
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