A system and method involving a coded modulation scheme whereby different spectral efficiencies can be achieved for different transmitters in a WDM system using the same M 2 -QAM modulation format. A maximum achievable spectral efficiency for the transmitters may be selected and a spectral efficiency step-size of the maximum achievable spectral efficiency may be specified. The spectral efficiency for any transmitter in the system may be individually selected by reducing its spectral efficiency from the maximum achievable spectral efficiencies by a selected number of steps corresponding to the step size.

Coded modulation for small step-size variable spectral efficiency

The invention applies to the image processing field, and provides a method and a system for image registration The method for the image registration includes steps: obtaining an image to be registered and a reference image; performing morphological processing on the image to be registered and the reference image, dividing the image to be registered into a plurality of sub-images to be registered, of the same size, and dividing the reference image into a plurality of reference sub-images of the same size; confirming an initial reference sub-image from the reference sub-images, setting a reference template according to the initial reference sub-image, registering the reference template with the sub-images to be registered, and obtaining initial offset according to a registration result; registering the sub-images to be registered according to the initial offset, and confirming whether an initial sub-image to be registered, after being registered, includes local offset through a bisection method; registering the image to be registered according to the initial offset and/ or the local offset The method and the system for the image registration can rapidly, and simply and conveniently register the image to be registered

Method and system for image registration

The invention discloses a remote sensing satellite multispectral image registration method. The remote sensing satellite multispectral image registration method comprises the following steps that 1, a rough registration image is obtained according to the distance of a multispectral detector; 2, histogram projection is carried out on an image to be registered on the basis of a reference image; 3, the two images are partitioned in blocks, and for each pair of image blocks, angular points of each pair of image blocks are extracted, and in order to realize registration of a near infrared image, the main direction phase coincidence characteristic of each block is extracted, and a positive and negative sub pixel matching point set of each block is obtained on the basis of phase correlation and surface fitting; 4, triangular grid partition is carried out on the reference image and the image to be registered, a transformation coefficient is worked out, and resampling is carried out on the image to be registered to obtain a registered image. Compared with the prior art, the method solves the problem that as the gray difference of features of different reflectivities on different spectral sections is large, registration is difficult, and also effectively solves the problem that large remote sensing images in different areas distort to different extents.

Remote sensing satellite multispectral image registration method

The object of the invention is to provide an image registration method and image registration equipment. The image registration method comprises steps that characteristic points of acquired annularly-arranged to-be-registered images are calculated; an initial relative offset vector between each two adjacent images of the annularly-arranged images is determined according to the characteristic points of the annularly-arranged to-be-registered images; the relative rotation angles of the annularly-arranged to-be-registered images and the relative offset vectors of the annularly-arranged to-be-registered images after being rotated by the above mentioned angles are determined according to the initial relative offset vectors. By introducing a priori model of image annular arrangement, the characteristic points of the various images of the model are calculated, and the initial relative offset vector between each two adjacent images of the annularly-arranged images is determined, and then the relative rotation angles of the annularly-arranged images are calculated by using the model information of the image annular arrangement in an actual condition and the initial relative offset vector between each two adjacent images of the annularly-arranged images, and therefore result errors are reduced after image registration.

Image registration method and image registration equipment

The invention discloses a hyperspectral image self-adaption lossless predictive encoding system and method based on edge information to mainly solve the problems that in the prior art, due to the fact that the edge information of a hyperspectral image is not taken into consideration in the decorrelation process, the compression decorrelation is not thorough and the compression ratio is limited. The implementation process of the hyperspectral image self-adaption lossless predictive encoding method includes the following steps of firstly, conducting inter-spectrum prediction on the hyperspectral image through a mid-value prediction algorithm based on opposite angles to obtain an inter-spectrum prediction residual error; secondly, conducting inter-spectrum prediction on the hyperspectral image through an inter-spectrum prediction algorithm based on the edge information to obtain an inter-spectrum prediction residual error; thirdly, selecting a final prediction mode for each spectrum section by comparing the prediction residual errors in two prediction modes; fourthly, conducting entropy coding on the prediction residual error corresponding to the final prediction mode to obtain a lossless compressed code stream. According to the system and the method, the edge information of the image is fully used, the decorrelation is thorough, a high lossless compression ratio is obtained, and the method and the system are suitable for hyperspectral data processing and transmission.

Hyperspectral image self-adaption lossless predictive encoding system and method based on edge information

The invention discloses an on-board non-registering multispectral image lossless/lossy encoding system and an on-board non-registering multispectral image lossless/lossy encoding method, and mainly solves problems of poor correlation between spectrums, inaccurate control of JPEG-LS (Joint Pho-tographic Experts Group-Lossless Standard) rate and low quality of image reconstruction caused by the fact that original on-board multispectral images are not registered in the prior art . The on-board non-registering multispectral image lossless/lossy encoding method includes: rearranging spectral segments of the non-registering multispectral images, registering each spectral segment of the multispectral images sequentially according to a sequence of optimal spectrum segment encoding, compressing the registered multispectral images in a lossless or lossy manner, selecting a prediction mode of a current encoding spectrum segment during lossy compressing, then performing JPEG-LS lossless compression on corresponding predicted residual, distributing object code rate of encoding spectrum segments during lossy compression, then selecting a prediction mode of current encoding spectrum segment to perform code-rate-controllable JPEG-LS lossless compression on corresponding predicted residual based on secondary iteration adjustment, and outputting code stream. The on-board non-registering multispectral image lossless/lossy encoding system and the on-board non-registering multispectral image lossless/lossy encoding method have the advantages of high compression performance and accurate rate control, and are applicable to various on-board multispectral data processing and transmission.

On-board non-registering multispectral image lossless/lossy encoding system and on-board non-registering multispectral image lossless/lossy encoding method

The invention discloses a method for multi-spectral image real-time registration based on covariance. The method mainly solves the problem that the real-time compression performance is affected due to no registration of a multi-spectral image shot by a satellite. The method comprises a first step of inputting reference waveband images and to-be-registered waveband image data; a second step of performing sampling calculation on the input data; a third step of performing covariance calculation on the data after sampling; a fourth step of determining a uniline offset through a covariance value worked out; a fifth step of judging whether block registration is finished according to an absolute value of the difference of the line offset calculated this time and the line offset calculated last time, and determining block offsets; a sixth step of finishing image registration of three reference spectrum sections and determining a final offset according to the three obtained block offsets; a seventh step of performing vertical offset on the non-registered image according to the final offset, and obtaining a final output image of multi-spectral image real-time registration. The method has the advantages of being simple to achieve and high in registration precision and can be used for registration calculation prior to multi-spectral image compression.

Method for multi-spectral image real-time registration based on covariance

The invention discloses a registration pre-processing system suitable for multispectral image compression, and mainly solves the problem that a multispectral image shot by a satellite influences the real-time compression property as not being subjected to registration. The system comprises an image input module (1), an image caching module (2), and a registration calculating module (3), wherein the image input module is used for reorganizing the auxiliary data generated by a panorama camera and the data of a multispectral image to be registered into image data suitable for systematic internal processing, as well as outputting the image data to the image caching module and the registration calculating module; the image caching module is used for caching the image data input by the image input module; the registration calculating module controls the image input module and the image caching module to upload data of a reference spectrum section and data of a spectrum section to be registered, utilizes the uploaded data for registration, and outputs the registered multispectral image to a lower-level system. The registration pre-processing system is easy to realize, can process in time, and improves the compression property of a post-system prominently, and can be used for registration pre-processing operation before the compression of the multispectral image shot by the satellite.

Registration pre-processing system suitable for multispectral image compression

Popular Tasks used by Researchers

How can I help with your research?

Get more enhanced response by uploading the PDFs you want me to reference.

No relevant PDFs in your library

SciSpace is the AI research assistant for academics. Run systematic literature reviews on 280M+ papers, and write papers with cited sources. Trusted by 1M+ students, PhDs & researchers.

SciSpace | AI for Research

We encountered an error while loading the panel. Please try refreshing the page.

Something went wrong

Analyze PDFs

Code & Manuscripts

Funding & Grants

Literature & Patents

Medical & Clinical Data

Systematic Review

Visualize & Present

Web & Data

Build a Google Scholar-like website for your research.

Build a website

Create charts and images for your research

Create a Chart

Write a paper for submission to a journal

Draft a manuscript

Patent Search

Design eye-catching scientific posters in minutes.

Scientific Poster Generation

Systematic Literature Review

Anyone with the link can view this chat. You can switch it back to private anytime.

One task is running at the moment. Your messages will be shown right after.

Drag and drop or click here to browse

Loved by <highlight>1 million+</highlight> researchers

Extract a list of specific topics and their sources from unstructured text

Topics

Compare and analyze relevant papers that matches with your search

Papers

Get insights from PDFs and bookmarked papers from your library

My library

Recent searches

Try searching for:

Catch AI-generated content in scholarly and non-scholarly content

{ai} Detector

Ai Writer

Get PDF Summaries, highlighted text explanations 

Chat with PDF

Effortlessly create in-text citations and bibliographies in APA and 2,500 other formats

Citation generator

Get explanations, summaries, and answers on academic papers

Ease up your research workflow with {scispace}'s cohort of exciting AI tools

Elevate your academic writing skills and convey your ideas the way you want

Paraphraser

Explore our range of reading and writing tools

Your file is being prepared and should be ready in a few minutes. If it's a large file, it might take a bit longer. You can close this window, and we'll email you the file when it's done.

You have reached a maximum limit of <strong>{limit}</strong> columns in the table. Remove at least <strong>1</strong> column to add or create another one.

Wang Keyan

Author Tools

Chat about Author

Papers

On-board non-registering multispectral image lossless/lossy encoding system and on-board non-registering multispectral image lossless/lossy encoding method

Method for multi-spectral image real-time registration based on covariance

Registration pre-processing system suitable for multispectral image compression