51 results about "Discrete sine transform" patented technology

Calculate the log frame energy value of each of a pre-determined number n of frames of an input speech signal and apply a matrix transform to the n log frame energy values to form a temporal matrix representing the input speech signal. The matrix transform may be a discrete cosine transform.

Provided is an apparatus and method for encoding and decoding using alternative transform units according to the correlation of residual signals. The video encoding apparatus includes a first transforming unit for performing discrete cosine transform (DCT), first quantization, first inverse quantization, and inverse DCT on a block basis onto residual coefficients generated after intra frame prediction or inter frame prediction; a second transforming unit for performing discrete sine transform (DST), second quantization, second inverse quantization, and inverse DST on a block basis onto the residual coefficients; a selecting unit for selecting one having a high compression rate between the first and second transforming units for each block through performing rate-distortion optimization; and a flag marking unit for recording information about the selected transforming unit at a flag bit provided on a macroblock basis.

An image encoding apparatus for application to images expressed as respective frames of a digital video signal, whereby an image is converted into an array of blocks with specific blocks predetermined as being independent internally encoded blocks and the remainder as predictively encoded blocks, with predicted pixel signal values for a predictively encoded block being derived by interpolation from pixel signal values of at least one pair of blocks which have been already encoded and enclose that predictively encoded block along the row or column directions or both the row and column directions. Encoding efficiency is enhanced by applying Discrete Sine Transform processing along the interpolation direction, when encoding an array of prediction error signal values derived for a block, and by executing adaptive prediction by determining an optimum interpolation direction, when there are two possible directions for deriving predicted pixel signal values for a block.

The invention provides an optimized video data coding method based on boundary adaptive transform. The method mainly comprises steps: according to the existing DCT (Discrete Cosine Transform) matrix for video coding, a new transform matrix is generated, the new transform matrix and the existing DST (Discrete Sine Transform)/DCT matrix are combined into a new transform matrix set; according to a prediction mode, the size of a transform unit, and the relationship between the boundary information of a transform unit and the boundary information of a prediction unit, a group of transform matrixes is selected from the new transform matrix set; and by using the group of new transform matrixes, inputted video data are transformed, and a coding stream is generated. The method of the invention makes full use of distribution characteristics of residual matrixes after inter-frame prediction, and based on the boundary information of the prediction unit and the transform unit, a different transform matrix is adopted for a different boundary characteristic to carry out transform. The optimized method can select a more efficient transform matrix for transform in a targeted mode according to the characteristics of residuals after inter-frame prediction, and the coding efficiency is thus improved.

The present invention relates to a method and apparatus for encoding and decoding a video image based on transform. The method for decoding a video includes: determining a transform mode of a current block; inverse-transforming residual data of the current block according to the transform mode of the current block; and rearranging the inverse-transformed residual data of the current block according to the transform mode of the current block, wherein the transform mode includes at least one of SDST (Shuffling Discrete Sine Transform), SDCT (Shuffling Discrete cosine Transform), DST (Discrete Sine Transform) or DCT (Discrete Cosine Transform).

A system and method for parallel computation of Discrete Sine and Cosine Transforms. The computing system includes a plurality of interconnected processors and corresponding local memories. An input signal x is received, partitioned into P local vectors x_i, and distributed to the local memories. The preprocessors may calculate a set of coefficients for use in computing the transform. The processors perform a preprocess in parallel on the input signal x to generate an intermediate vector y. The processors then perform a Fast Fourier Transform in parallel on the intermediate vector y, generating a second intermediate vector a. Finally, the processors perform a post-process on the second intermediate vector a, generating a result vector v, the Discrete Transform of signal x. In one embodiment, the method generates the Discrete Sine Transform of the input signal x. In another embodiment, the method generates the Discrete Cosine Transform of the input signal x.

Systems and methods for robust recognition of machine-readable symbols from highly blurred or distorted images. An image signal representation of a machine-readable symbol element is transformed into a different space using one or more transform operations, which moves an n-dimensional vector of measured light intensities into another n-dimensional space. The types of transform operations may include blur robust orthonormal bases, such as the Discrete Sine Transform, the Discrete Cosine Transform, the Chebyshev Transform, and the Lagrange Transform. A trained classifier (e.g., an artificial intelligence machine learning algorithm) may be used to classify the transformed signal in the transformed space. The types of trainable classifiers that may be used include random forest classifiers, Mahalanobis classifiers, support vector machines, and classification or regression trees.

The invention discloses a method for built-in steganography of an H.265 video. Information embedding is carried out for the DST (Discrete Sine Transform) coefficient of a 4*4 luminance residual block. First, two directions of distortion drift are determined according to the intra-frame prediction mode of an H.265 video. Then, a triple of a corresponding format is selected for information embedding according to the specific direction of distortion drift. As the triple used has a coefficient compensation effect, 4*4 luminance block pixels causing distortion drift do not change during inverse transformation of the embedded DST coefficient of the residual block, and the purpose of distortion drift control during built-in steganography is achieved. Experimental results show that the method for built-in steganography of an H.265 video provided by the invention can effectively control intra-frame distortion drift, and has good visual imperceptibility and a good visual effect.

A more efficient encoder/decoder is provided in which an N-point MDCT transform is mapped into smaller sized N/2-point DCT-IV, DST-IV and/or DCT-II transforms. The MDCT may be systematically decimated by factor of 2 by utilizing a uniformly scaled 5-point DCT-II core function as opposed to the DCT-IV or FFT cores used in many existing MDCT designs in audio codecs. Various transform factorizations of the 5-point transforms may be implemented to more efficiently implement a transform.

The invention discloses a SPEED fast magnetic resonance imaging method based on discrete cosine transform. The SPEED fast magnetic resonance imaging method based on discrete cosine transform mainly includes the steps of k space data collection, zero fill Fourier reestablishment, discrete cosine transform, discrete cosine transform domain double-layer sparse ghost model determining, overlapped ghost separation based on LSE, discrete cosine inverse transformation, registering and summation of a plurality of ghost sub-images and image reconstruction. By means of the SPEED fast magnetic resonance imaging method, discrete cosine transform can be used for SPEED data sparse representation and improve image sparseness, and accordingly quality of a SPEED reconstructed image is improved.

The invention relates to an encryption algorithm of encryption OFDM (Orthogonal Frequency Division Multiplexing) based on discrete Hartley transform, and belongs to the technical fields of information communication and signal processing. Compared with the conventional OFDM system, an IFFT (Inverse Fast Fourier Transform) module which is necessary in an OFDM system is omitted, and the complexity of the system is reduced. At the same time, the diversity gain of frequency selectivity of the system is increased, and the anti-fading performance and the capacity of the system are improved.

The invention belongs to the field of nuclear detection processing in nuclear technique exploration, in particular to a discrete cosine neural-network fuzzy noise reduction method for nuclear detection data, and aims to effectively reduce noise in gamma spectrum data. The method includes the steps: subjecting spatial data formed by nuclear detection signal data to discrete cosine transform to obtain frequency spectrum data in a discrete cosine domain; subjecting the nuclear detection data to filtering and inverse discrete cosine transform in the discrete cosine domain to obtain primary noise reduction result; establishing a neural network, inputting a sample by using the nuclear detection signal data as nodes in the neural network, and estimating parameters of a membership function in the neutral network by means of least squares back-propagation to obtain final noise reduction result output by the neural network. The method is capable of well recognizing noise signals, network model parameters are regulated and optimized according to noise signal features, the noise in the signal data is reduced effectively, and signal-to-noise ratio of the nuclear detection data is increased greatly.

The invention relates to a method for coding and rebuilding an image block in video coding. A coding process comprises the following steps of: generating an image prediction block according to a prediction mode selected by a current block; selecting a group of low-complexity integer DST (Discrete Sine Transform) functions to transform a residual block so as to obtain a transformation ratio block; and quantizing the transformation ratio block. A rebuilding process comprises the following steps of: receiving the quantized transformation ratio block; carrying out inverse quantization to obtain a transformation ratio block; selecting a group of low-complexity integer DST functions to inverse transform the transformation ratio block; calculating to obtain a residual block; generating an image prediction block according to a prediction mode selected by a current block; and combining with the residual block calculated through inverse transformation to generate a rebuilt image block. According to the method, DST without multiplication is realized, has approximately the same performances as those of MDDT (Mode-dependent Directional Transform), but the storage complexity of a coder and a decoder is obviously reduced, so the method can be directly applied in a video coding process, so that the coding efficiency is effectively improved, and the computation complexity of relevant mode transformation is reduced.

The invention discloses a fluid animation rendering method based on detail capturing and form correcting in the technical field of computer image processing. The method comprises the following steps of: performing fluid simulation and optimizing a speed field in an initial scene according to a Navier-Stokes equation; updating a corresponding density field and a corresponding temperature field according to the optimized high-precision speed field by adopting a semi-Lagrangian method so as to be used for rendering and next-frame simulating; and finally, rendering an updated density field into a fluid animation. More colorful details can be captured through a high-speed discrete sine transform operator, the calculation scale of a part with highest time consumption in an original simulation method can be reduced through using a down-sampling or octree method, simultaneously the result is corrected, and the functions of increasing the simulation speed and keeping fluid simulation details are realized. Compared with the prior art, according to the method, the simulation speed is relatively high, and the fluid simulation details with high more accuracy can be acquired.

The invention discloses a rice pest intelligent recognition and classification method based on principal component analysis. According to the method, discrete sine transform (DST) and modular 2-dimension principal component analysis (modular 2D PCA) are combined to achieve rice pest image intelligent recognition. The method includes the steps that firstly, rice pest images are subjected to the DST and then are compressed, IDST is performed on the images to reestablish images to filter out high-frequency parts insensitive to human eyes; secondly, rice pest feature extraction and mode recognition are performed through the modular 2D PCA method. Accordingly, the method plays an important role in reducing feature dimensions and maintaining illumination, colors, gestures and other insensitive classification features. According to the rice pest intelligent recognition and classification system, images shot by digital cameras can be applied to computer programs to be processed, unknown pest images can be automatically compared with training sample database pest images in a data storer through Matlab software, and then recognition results can be output to a display.