265 results about "Discrete cosine transforms" patented technology

An efficient digital video (DV) decoder process that utilizes a specially constructed quantization matrix allowing an inverse quantization subprocess to perform parallel computations, e.g., using SIMD processing, to efficiently produce a matrix of DCT coefficients. The present invention utilizes a first look-up table (for 8x8 DCT) which produces a 15-valued quantization scale based on class number information and a QNO number for an 8x8 data block ("data matrix") from an input encoded digital bit stream to be decoded. The 8x8 data block is produced from a deframing and variable length decoding subprocess. An individual 8-valued segment of the 15-value output array is multiplied by an individual 8-valued segment, e.g., "a row," of the 8x8 data matrix to produce an individual row of the 8x8 matrix of DCT coefficients ("DCT matrix"). The above eight multiplications can be performed in parallel using a SIMD architecture to simultaneously generate a row of eight DCT coefficients. In this way, eight passes through the 8x8 block are used to produce the entire 8x8 DCT matrix, in one embodiment consuming only 33 instructions per 8x8 block. After each pass, the 15-valued output array is shifted by one value position for proper alignment with its associated row of the data matrix. The DCT matrix is then processed by an inverse discrete cosine transform subprocess that generates decoded display data. A second lookup table can be used for 2x4x8 DCT processing.

A method is adapted for compressing an image data block, and includes the steps of:(a) subjecting the image data block to discrete cosine transformation so as to generate discrete cosine transform data;(b) quantizing the discrete cosine transform data in accordance with a quantizer matrix that consists of an array of quantizing coefficients so as to generate quantized data;(c) encoding the quantized data using an entropy coding algorithm so as to generate an encoded bitstream; and(d) when the length of the encoded bitstream does not fall within a predetermined range, adjusting the quantizing coefficients in the quantizer matrix and repeating steps (b) and (c) until the length of the encoded bitstream falls within the predetermined range.

A system providing methods for improved compression of images that have been compressed using Discrete Cosine Transform (DCT) based compression is described. A digital image that has been compressed using DCT based compression, such as an image compressed using the Joint Photographic Experts Group (JPEG) compression scheme, is received and partially decompressed to generate DCT coefficients of the image. The decoded coefficients of the image are then rearranged to aggregate like frequencies together. After rearrangement, the image is recompressed using a wavelet-based compression scheme.

The invention discloses an insurance claim antifraud implementation method based on a claim photo deep learning. The method comprises: when a claim photo submitted by a user is received, performing frequency-domain transforming on the acquired photo based on a two-dimensional discrete cosine transform function, and according to a preset analysis rule and based on a color value of the photo subjected to the frequency-domain transforming in each color channel, performing authenticity verification on the photo; if the acquired photo are unreal, generating reminding information to remind that a fraudulent conduct exists in a claim application corresponding to the acquired photo; if the acquired photo is real, identifying photographing time of the acquired photo; extracting claim event occurrence time filled in the claim application corresponding to the acquired photo; and when the extracted claim event occurrence time does not match with the identified photographing time, generating reminding information to remind that the fraudulent conduct exists in the claim application corresponding to the acquired photo; The present invention also provides a server applicable to the method. The method can automatically identify a fraudulent claim behavior.

The present invention relates to a method and an apparatus for transform-based image encoding / decoding. The image decoding method according to the present invention comprises: a step of determining atransform mode of a current block; a step of inversely transforming residual data of the current block according to the transform mode of the current block; and a step of rearranging the residual dataof the current block inversely transformed according to the transform mode of the current block, wherein the transform mode may include at least one of a shuffling discrete sine transform (SDST), a shuffling discrete cosine transform (SDCT), a discrete sine transform (DST) and a discrete cosine transform (DCT).

Disclosed is a visual scan method using scan table capable of determining an exact scan method according to blocks in discrete cosine transform (DCT) even in special circumstances, and a discrete cosine transform device employing the same method. The discrete cosine transform device includes: a scan table generation section for accumulatively summing absolute values of the coefficients obtained through a DCT operation, in such a manner that the absolute values in pixels located at the same position of each unit video block in a predetermined video block group are summed together by the predetermined video block group with respect to an input video, and then for generating a scan table according to the magnitudes of the summed absolute values; a bit-rate calculation section for calculating an amount of bits by accumulatively summing only bit lengths of a variable length coding (VLC) table, the VLC table being obtained from the values arranged according to the scan table generated in the scan table generation section; and a scan control section for receiving the input video having been discrete-cosine-transformed, inputting the received video to the scan table generation section to generate a scan table by the predetermined video block group, receiving a value of a bit rate according to generation of the scan table from the bit-rate calculation section, and performing a control operation using capacity increase of the scan table and the bit rate to provide a scan table for scanning according to the scan method.

A non-uniform image defect inspection method includes steps of inputting an original two-dimensional image; separating a non-uniform background image from the original two-dimensional image by Discrete Cosine Transform (DCT) to obtain a residual image without the non-uniform background image; binarization segmenting the residual image to extract defects from the residual image, wherein the segmented defects are the inspection results.

A multi-view distributed video compression side information generation method facing to a wireless multi-media sensing network is a technical scheme directing to multi-media multi-view data compression in the wireless multi-media sensing network. The method comprises extracting discrete cosine transform (DCT) low frequency coefficients in an area-of-interest (ROI) macro block of a non-key frame (Wyner-Zicframe, WZ) in a main visual angle to conduct entropy coding and decoding, using received the DCT low frequency coefficients to conduct both-way motion estimation interpolation on the decoding end of the ROI macro block to generate ROI macro block side information, using encoded frames to conduct motion compensation frame interpolation (or extrapolation) on a non-ROI area to generate non-ROI macro block side information, and further generating best non-key frame time side information. Space side information is generated by using a homography matrix method. Finally the time side information and the space side information are merged. By means of the improvement, code rate is reduced, quality of decoding images is improved, energy consumption of sensor nodes is reduced, and service life of the wireless sensor network is prolonged.

A method is disclosed for performing a discrete cosine transform (DCT) using a microprocessor having an instruction set that includes SIMD floating point instructions. In one embodiment, the method includes: (1) receiving a block of integer data having C columns and R rows; and (2) for each row, (a) loading the row data into registers; (b) converting the row data into floating point form so that the registers each hold two floating point row data values; and (c) using SIMD floating point instructions to perform weighted-rotation operations on the values in the registers. Suitable SIMD floating point instructions include the pswap, pfmul, and pfpnacc instructions. For the row-DCT, the data values are preferably ordered in the registers so as to permit the use of these instructions. For the column-DCT, two columns are preferably processed in parallel using SIMD instructions to improve computational efficiency. An intermediate buffer may be used to avoid unnecessary conversions between integer and floating point format.

A method and system for arbitrary resizing of a compressed image in the discrete cosine transform (DCT) domain. First and second scaling parameters P and Q a re determined in accordance with the block numbers L and M and the scaling rati o L / M or M / L. A non-uniform, or uneven, sampling in the DCT domain is then applied to coefficients of successive blocks in the compressed image in accordance with the scaling parameters. In an embodiment, P blocks are sampled and transformed from a given block length to |P| according to a |P|-point IDCT, while Q blocks are sampled and transformed from a given block length to |Q| according to a |Q|-point IDCT. The non- uniformly sampled and transformed pixel domain samples are then regrouped into a predetermined block size and transformed back to generate the DCT coefficient of the compressed image. The proposed method significantly reduces the computational complexity compared with other DCT domain arbitrary ratio image resizing approach. It also facilitates the practical implementations since only the fast implementations of IDCT with length N (1 < N < 9) and DCT with length 8 are required.

This invention relates to the design and implementation of a large family of fast, efficient, hardware-friendly fixed-point multiplierless inverse discrete cosine transforms (IDCT) and the corresponding forward transform counterparts. All of the proposed structures comprises of butterflies and dyadic-rational lifting steps that can be implemented using only shift-and-add operations. The approach also allows the computational scalability with different accuracy-versus-complexity trade-offs. Furthermore, the lifting construction allows a simple construction of the corresponding multiplierless forward DCT, providing bit-exact reconstruction if properly pairing with our proposed IDCT. With appropriately-chosen parameters, all of the disclosed structures can easily pass IEEE-1180 test. The high-accuracy algorithm of the present invention is over 100 times more accurate than IEEE-1180 specifications, leading to practically drifting-free reconstruction in popular MPEG-2 and MPEG-4 codecs even at the lowest quantization setting.

The invention relates to a morphological component analysis (MCA)-based synthetic aperture radar (SAR) image noise suppression method. The method is technically characterized in that: an MCA method is applied to the suppression of multiplicative noises in an SAR image; and because the image generally comprises the two morphological components of edge / contour and texture, in the method, the dictionary assembly of curvelet and local discrete cosine transform (LDCT) is utilized under the uniform frame of MCA according to the good edge / contour representation characteristics of the curvelet and the high partial texture expression capability of the LDCT to fulfill the aim of suppressing the noises in the SAR image. Therefore, for a noise image, effective components of the image can be separated and the noises are kept in the remnant image by the method to fulfill the aim of suppressing the noises. Experimental results on both simulated and real SAR images show that the method has the advantage of relatively better noise suppression effect compared with the conventional wavelet-based methods and curvelet-based methods.