9 results about "Integer wavelet transform" patented technology

The invention discloses a robust reversible watermarking method based on BFMs and adaptive normalization. The method comprises the steps of watermark embedding and watermark extraction. The watermark embedding specifically comprises the steps of generating watermark sequence information, performing integer wavelet transform on a carrier image, extracting a low-frequency region, and calculating BFMs of the low-frequency region; a proper watermark pair is selected through a private key, self-adaptive normalization is carried out according to the watermark pair, and the watermark is embedded in the normalized amplitude; reconstructing an image based on the amplitude of the embedded watermark; constructing a final reversible watermark image based on the reconstructed image; watermark extraction: judging whether the image is attacked or not; for an unattacked image, carrying out watermark extraction based on the auxiliary information; for an attacked image, watermark extraction is carried out by calculating the BFMs of the attacked image. The method has noise resistance and also has relatively good image reconstruction capability.

The application discloses a compression method of marine grid data, and relates to the field of data processing.The method first performs mask calculation on target grid data, extracts a mask matrix and performs compression, so that position information of marine and land grids is separately stored, and the compression process of marine data is prevented from being disturbed by land data.Marine grid data is screened out according to the mask matrix, integer wavelet transformation is performed on the preprocessed data, and the wavelet transformation result is twice compressed by using run-length encoding and entropy encoding, so that the best compression ratio is achieved.Finally, the generated secondary compression file and the mask compression file are merged to form a final compression file.The application can achieve a higher compression ratio, meanwhile, ensures the quality and integrity of the data in the recovery process, and significantly improves the data storage and transmission efficiency.

This invention relates to a data flow feature identification method and system for high-orbit satellite networks, belonging to the field of satellite internet and onboard network traffic engineering technology. The method includes the following steps: Step 1, extracting detailed coefficients of the traffic sequence and updating the macroscopic congestion status flag through threshold comparison; Step 2, triggering dynamic sampling based on the congestion status and extracting the initial segment of the payload as the sample to be evaluated; Step 3, statistically analyzing the frequency of sample bytes and accumulating mapping values ​​based on a pre-set lookup table to obtain an approximate Shannon entropy; Step 4, adaptively updating the dynamic sampling span based on the difference between the current and historical entropy values ​​and the congestion status. This scheme significantly reduces onboard computing power overhead. By introducing a denormalized integer wavelet transform probe and an entropy dimensionality reduction calculation mechanism based on a pre-set lookup table, it avoids intensive floating-point and logarithmic operations at the algorithm's underlying level, greatly reducing the consumption of limited processor resources on high-orbit satellites.

The invention relates to the technical field of communication security, and discloses an image encryption method and system based on compressed sensing and dynamic embedding, and the method comprises the steps: generating an initial value of a four-dimensional hyperchaotic system according to a to-be-encrypted plaintext image and an external random number; iterating the four-dimensional hyperchaotic system by using the initial value to obtain a plurality of groups of chaotic sequences; obtaining a sparse scrambling matrix based on the plaintext image; obtaining a quantization matrix by using multiple groups of chaos sequences and the sparse scrambling matrix; executing scrambling operation on the quantization matrix based on multiple groups of chaos sequences to obtain a scrambling matrix; performing dynamic bidirectional diffusion operation on the scrambling matrix by using multiple groups of chaotic sequences to obtain a ciphertext image; and performing integer wavelet transform and local texture energy analysis processing on the carrier image to construct a dynamic embedding mechanism, decomposing the ciphertext image, and adaptively embedding the decomposed ciphertext image into a high-frequency sub-band of the carrier image to obtain a secret-carrying image. The dynamic safety, the sampling efficiency and the visual concealment are effectively improved.

The invention provides a medical image content adaptive encryption method based on chaotic mapping, which relates to the technical field of digital information security, and comprises the following steps: firstly, identifying a region of interest of a medical image, and executing differential integer wavelet transform to obtain a frequency domain coefficient; secondly, by calculating a local texture entropy index and a tissue self-similarity degradation index, the system can accurately quantify the pathological feature richness and the suspected lesion degree of each image block. And dynamically adjusting chaotic system parameters, and generating a first key stream bound with the local texture entropy index and the organization self-similarity degradation index. And then, triggering a visual retention or privacy shielding mode based on the frequency domain sub-band attribute: not encrypting the LL sub-band to retain the anatomical contour, and respectively executing adaptive chaotic encryption with different high and low iteration round numbers on the LH / HL and HH sub-bands. According to the method, the dynamic protection of one graph and one secret is realized, and the pathological privacy protection intensity and the clinical film reading retrieval efficiency are effectively balanced.

The application discloses an asymmetric visual meaningful image encryption method based on 2D compressive sensing. The method takes a plaintext image as an image to be encrypted, extracts plaintext parameters from the plaintext image, and encrypts the plaintext parameters into public parameters; takes the plaintext parameters and the public parameters as input values to generate initial values of a chaotic system, iterates the chaotic system to generate a chaotic sequence; indexes and scrambles the plaintext image to obtain a mapping image; uses a measurement matrix and the mapping image to perform 2D compressive sensing, quantization operation and diffusion encryption to obtain a ciphertext image; and performs decimal bit decomposition on the ciphertext image, performs integer wavelet transform, scrambling encryption, embedding hiding, inverse scrambling and inverse integer wavelet transform on a carrier image to obtain a visual meaningful encrypted image. The plaintext image is encrypted to obtain the visual meaningful encrypted image by combining 2D compressive sensing, so that the image encryption effect and security are improved.

The invention discloses an anti-error robust image steganography method based on background-noise-free low-frequency embedding, and the method comprises the steps: carrying out the preprocessing and hybrid coding of an original secret image, and generating a final secret embedded stream; 5 / 3 integer wavelet transform is carried out on the carrier image to decompose the frequency domain, a first-level low-frequency sub-band is extracted, texture activity is calculated in a blocking mode, and an embedded mask is generated; modulating and setting a quantization step size and a jitter bias based on a quantization index, and adjusting a block mean value and superposing an offset based on a bit to be embedded to complete embedding; the method comprises the following steps: performing integer wavelet transform and block statistics on a received image, obtaining an initial bit stream by using a minimum distance method of quantization index modulation, and reconstructing and outputting a secret image through anti-interleaving, error correction decoding, inverse whitening and inverse scrambling processing. According to the method, the problems of poor safety and weak burst error resistance of traditional steganography are solved, the balance of robustness and concealment is realized, and the reliability of covert communication under a complex channel is improved.

This invention discloses an error-resistant robust image steganography method based on low-frequency embedding without background noise. The method includes: preprocessing and hybrid encoding the original secret image to generate a final secret embedding stream; performing a 5 / 3 integer wavelet transform on the carrier image to decompose the frequency domain, extracting the first-level low-frequency sub-band, calculating texture activity in blocks, and generating an embedding mask; setting the quantization step size and jitter bias based on quantization index modulation, adjusting the block mean based on the bits to be embedded, and superimposing the offset to complete the embedding; performing integer wavelet transform and block statistics on the received image, obtaining the initial bit stream using the minimum distance method of quantization index modulation, and reconstructing the output secret image through deinterleaving, error correction decoding, inverse whitening, and inverse scrambling. This invention solves the problems of poor security and weak resistance to burst errors in traditional steganography, achieving a balance between robustness and concealment, and improving the reliability of covert communication in complex channels.

The application discloses an image hiding method and device based on compressed sensing and run-length coding. The method first compresses the size of a secret image needing security protection by using compressed sensing technology, then converts the decimal pixel value of the size-compressed secret image into a binary sequence, then compresses the binary sequence by using run-length coding to obtain a numerical sequence with a shorter length, and converts a cover image in a spatial domain into a frequency domain by using integer wavelet transform to obtain four subbands. The numerical sequence compressed twice has a similar form with the high-frequency subband coefficients of the cover image, and can directly replace the high-frequency subband coefficients to complete embedding operation. The application ingeniously combines compressed sensing, run-length coding and high-frequency subband embedding technology, greatly improves the quality of the camouflage image under the premise of ensuring high hiding capacity, and has the advantages of high capacity, low complexity and the like.