Abstract: In general, techniques are described for implementing a 16-point inverse discrete cosine transform (IDCT) that is capable of applying multiple IDCTs of different sizes. For example, an apparatus comprising a 16-point inverse discrete cosine transform of type II (IDCT-II) unit may implement the techniques of this disclosure. The 16-point IDCT-II unit performs these IDCTs-II of different sizes to transform data from a spatial to a frequency domain. The 16-point IDCT-II unit includes an 8-point IDCT-II unit that performs one of the IDCTs-II of size 8 and a first 4-point IDCT-II unit that performs one of the IDCTs-II of size 4. The 8-point IDCT-II unit includes the first 4-point DCT-II unit. The 16-point IDCT-II unit also comprises an inverse 8-point DCT-IV unit that includes a second 4-point IDCT-II unit and a third 4-point IDCT-II unit. Each of the second and third 4-point IDCT-II units performs one of the IDCTs-II of size 4.

Abstract: In general, techniques are described for implementing a 16-point discrete cosine transform (DCT) that is capable of applying multiple IDCT of different sizes. For example, an apparatus comprising a 16-point discrete cosine transform of type II (DCT-II) unit may implement the techniques of this disclosure. The 16-point DCT-II unit performs these DCTs-II of different sizes to transform data from a spatial to a frequency domain. The 16-point DCT-II unit includes an 8-point DCT-II unit that performs one of the DCTs-II of size 8 and a first 4-point DCT-II unit that performs one of the DCTs-II of size 4. The 8-point DCT-II unit includes the first 4-point DCT-II unit. The 16-point DCT-II unit also comprises an 8-point DCT-IV unit that includes a second 4-point DCT-II unit and a third 4-point DCT-II unit. Each of the second and third 4-point DCT-II units performs one of the DCTs-II of size 4.

Abstract: In general, techniques are described that provide for 4×4 transforms for media coding. A number of different 4×4 transforms are described that adhere to these techniques. As one example, an apparatus includes a 4×4 discrete cosine transform (DCT) hardware unit. The DCT hardware unit implements an orthogonal 4×4 DCT having an odd portion that applies first and second internal factors (C, S) that are related to a scaled factor (?) such that the scaled factor equals a square root of a sum of a square of the first internal factor (C) plus a square of the second internal factor (S). The 4×4 DCT hardware unit applies the 4×4 DCT implementation to media data to transform the media data from a spatial domain to a frequency domain. As another example, an apparatus implements a non-orthogonal 4×4 DCT to improve coding gain.

Abstract: Compression of audio signal data is described herein. In various embodiments, the compression of each unit of the audio signal data includes the employment of a distribution substantially representative of a subblock of residual data of the unit of audio signal data, to reduce the amount of data having to be transmitted to transmit the unit of audio signal data to a recipient.

Abstract: Techniques are disclosed for performing robust feature matching for visual search. An apparatus comprising an interface and a feature matching unit may implement these techniques. The interface receives a query feature descriptor. The feature matching unit then computes a distance between a query feature descriptor and reference feature descriptors and determines a first group of the computed distances and a second group of the computed distances in accordance with a clustering algorithm, where this second group of computed distances comprises two or more of the computed distances. The feature matching unit then determines whether the query feature descriptor matches one of the reference feature descriptors associated with a smallest one of the computed distances based on the determined first group and second group of the computed distances.

Abstract: HARQ parameters (e.g., maximum HARQ retransmission values) may be adapted. Cross-layer control and/or logical channel control may be used to select a maximum number of HARQ retransmissions, for example based on packet priority and/or QCI values. Respective priorities of video packets may be used to select one of a plurality of logical channels associated with a video application that may be established at a source wireless hop and/or a destination wireless hop. The logical channels have different HARQ characteristics. Different maximum HARQ retransmission values may be determined for select logical channels, for example such that packets of different priorities may be transmitted over different logical channels. One or more of the channels may be associated with one or more transmission queues that may have different priority designations. Video packets may be reordered (e.g., with respect to transmission order) within the transmission queues, for example in accordance with respective HARQ parameters.

Abstract: Methods, apparatuses and systems for performing hierarchical traffic differentiation and/or employing hierarchical traffic differentiation are provided. These methods, apparatuses and systems may be implemented to, for example, handle congestion and/or to manage user quality of experience (QoE). Performing the hierarchical traffic differentiation may include differentiating or otherwise classifying (collectively “differentiating”) traffic mapped to, or within, a bearer formed in accordance with a QoS class into multiple traffic sub-classes. Employing the hierarchical traffic differentiation may include scheduling and/or policing (e.g., filtering) the differentiated traffic for transmission based on a prioritization of, and/or policy for managing, the multiple traffic sub-classes.

Abstract: A method for generating a feature descriptor is provided. A set of pre-generated sparse projection vectors is obtained. A scale space for an image is also obtained, where the scale space having a plurality scale levels. A descriptor for a keypoint in the scale space is then generated based on a combination of the sparse projection vectors and sparsely sampled pixel information for a plurality of pixels across the plurality of scale levels.

Abstract: A product of an integer value and an irrational value may be determined by a sign-symmetric algorithm. A process may determine possible algorithms that minimize metrics such as mean asymmetry, mean error, variance of error, and magnitude of error. Given an integer variable x and rational dyadic constants that approximate the irrational fraction, a series of intermediate values may be produced that are sign-symmetric. The intermediate values may include a sequence of addition, subtraction and right shift operations the when summed together approximate the product of the integer and irrational value. Other operations, such as additions or subtractions of 0s or shifts by 0 bits may be removed.

Abstract: In general, techniques are described for coding data defining a sequence using one-to-one codes. An apparatus comprising a processing unit and a storage unit may implement the techniques. The processing unit decodes the index using a combinatorial enumeration process to generate a sequence. The index identifies the sequence in an array of all possible sequences ordered according to probabilities of the possible sequences assuming the possible sequences are produced by a memoryless source. The combinatorial enumeration process reorders sequences from the memoryless source according to the corresponding probabilities. The storage unit stores the sequence.

Abstract: In a particular embodiment, a method includes applying a first feature detector to a portion of an image to detect a first set of features. The first set of features is used to locate a region of interest, and a boundary corresponding to the region of interest is determined. The method also includes displaying the boundary at a display. In response to receiving user input to accept the displayed boundary, a second feature detector is applied to an area of the image encapsulated by the boundary.

Abstract: Techniques for efficiently performing full and scaled transforms on data received via full and scaled interfaces, respectively, are described. A full transform is a transform that implements the complete mathematical description of the transform. A full transform operates on or provides full transform coefficients. A scaled transform is a transform that operates on or provides scaled transform coefficients, which are scaled versions of the full transform coefficients. The scaled transform may have lower computational complexity whereas the full transform may be simpler to use by applications. The full and scaled transforms may be for a 2D IDCT, which may be implemented in a separable manner with 1D IDCTs. The full and scaled transforms may also be for a 2D DCT, which may be implemented in a separable manner with 1D DCTs. The 1D IDCTs and 1D DCTs may be implemented in a computationally efficient manner.

Abstract: In general, techniques are described for coding blocks of data using a generalized form of Golomb codes. In one example, a device may implement these techniques for encoding data that includes samples, each of which includes a set of values. The device includes a lossless coding unit. This lossless coding unit comprises a sample summation unit that computes a sum of the values of a first one of the samples and a counting unit that determines a sample index. The lossless coding unit further includes a variable length coding unit that codes the computed sum using a variable-length code to generate a coded sum and a uniform coding unit that codes the determined sample index using a uniform code to generate a coded sample index. The lossless coding unit also includes a format unit that combines the coded sum and the coded sample index to form a bitstream.

Abstract: A product of an integer value and an irrational value may be determined by a sign-symmetric algorithm. A process may determine possible algorithms that minimize metrics such as mean asymmetry, mean error, variance of error, and magnitude of error. Given an integer variable x and rational dyadic constants that approximate the irrational fraction, a series of intermediate values may be produced that are sign-symmetric. The intermediate values may include a sequence of addition, subtraction and right shift operations the when summed together approximate the product of the integer and irrational value. Other operations, such as additions or subtractions of 0s or shifts by 0 bits may be removed.

Abstract: In general, techniques are described that provide for 4×4 transforms for media coding. A number of different 4×4 transforms are described that adhere to these techniques. As one example, an apparatus includes a 4×4 discrete cosine transform (DCT) hardware unit. The DCT hardware unit implements an orthogonal 4×4 DCT having an odd portion that applies first and second internal factors (C, S) that are related to a scaled factor (?) such that the scaled factor equals a square root of a sum of a square of the first internal factor (C) plus a square of the second internal factor (S). The 4×4 DCT hardware unit applies the 4×4 DCT implementation to media data to transform the media data from a spatial domain to a frequency domain. As another example, an apparatus implements a non-orthogonal 4×4 DCT to improve coding gain.

Abstract: Techniques for efficiently performing full and scaled transforms on data received via full and scaled interfaces, respectively, are described and comprise (1) performing a first transform on a block of first input values to obtain a block of first output values by scaling the block to obtain scaled input values, performing a scaled one-dimensional (1D) transform on each row of the block, and performing a scaled 1D transform on each column of the block; and (2) performing a second transform on a block of second input values to obtain a block of second output values by performing a scaled 1D transform on each row of the block, performing a scaled 1D transform on each column of the block, and scaling the block.

Abstract: In general, techniques are described for implementing an 8-point discrete cosine transform (DCT). An apparatus comprising an 8-point discrete cosine transform (DCT) hardware unit may implement these techniques to transform media data from a spatial domain to a frequency domain. The 8-point DCT hardware unit includes an even portion comprising factors A, B that are related to a first scaled factor (?) in accordance with a first relationship. The 8-point DCT hardware unit also includes an odd portion comprising third, fourth, fifth and sixth internal factors (G, D, E, Z) that are related to a second scaled factor (?) in accordance with a second relationship. The first relationship relates the first scaled factor to the first and second internal factors. The second relationship relates the second scaled factor to the third internal factor and a fourth internal factor, as well as, the fifth internal factor and a sixth internal factor.

Abstract: A method for feature matching in image recognition is provided. First, image scaling may be based on a feature distribution across scale spaces for an image to estimate image size/resolution, where peak(s) in the keypoint distribution at different scales is used to track a dominant image scale and roughly track object sizes. Second, instead of using all detected features in an image for feature matching, keypoints may be pruned based on cluster density and/or the scale level in which the keypoints are detected. Keypoints falling within high-density clusters may be preferred over features falling within lower density clusters for purposes of feature matching. Third, inlier-to-outlier keypoint ratios are increased by spatially constraining keypoints into clusters in order to reduce or avoid geometric consistency checking for the image.

Abstract: Various arrangements for using a k-dimensional tree for a search are presented. A plurality of descriptors may be stored. Each of the plurality of descriptors stored is linked with a first number of stored dimensions. The search may be performed using the k-dimensional tree for one or more query descriptors that at least approximately match one or more of the plurality of descriptors linked with the first number of stored dimensions. The k-dimensional tree may be built using the plurality of descriptors wherein each of the plurality of descriptors is linked with a second number of dimensions when the k-dimensional tree is built. The second number of dimensions may be a greater number of dimensions than the first number of stored dimensions.

Abstract: Techniques are described to approximate computation of an inverse discrete cosine transform using fixed-point calculations. According to these techniques, matrixes of scaled coefficients are generated by multiplying coefficients in matrixes of encoded coefficients by scale factors. Next, matrixes of biased coefficients are generated by adding a midpoint bias value to a DC coefficient of the matrix of scaled coefficients. Fixed-point arithmetic is then used to apply a transform to the matrixes of biased coefficients. Values in the resulting matrixes are then right-shifted in order to derive matrixes of pixel component values. Matrixes of pixel component values are then combined to create matrixes of pixels. The matrixes of pixels generated by these techniques closely resemble matrixes of pixels decompressed using the ideal inverse discrete cosine transform (“IDCT”).