Abstract: Methods and systems for efficient scaling in the transform domain are provided when transform coefficient data is provided as an input to a data processing system, comprising generating a first matrix from transform coefficient data; zeroing out a row or column of, or inserting a row or column of zeros into, the first matrix; generating a second matrix by applying a one-dimensional inverse transform to the first matrix with the zeroed-out at least one row, the at least one column, the inserted at least one row of zeros or the at least one column of zeros; generating a third matrix by regrouping the second matrix; generating a combined matrix by applying a forward transform to the third matrix; and the data processing system scaling the data represented by the transform coefficient data by applying the combined matrix to the transform coefficient data.

Abstract: A method and system for efficient scaling in the transform domain, wherein transform coefficient data is provided as an input to a data processing system and scaled in the transform domain by application of a combined matrix. Some embodiments utilize discrete cosine transform data. One embodiment of the invention generates a combined matrix for one-dimensional scaling by selecting a rational scaling factor and matrix dimension value, generating a matrix with some zero values, applying a one-dimensional inverse transform, regrouping, and applying a one-dimensional forward transform. One application of the invention performs up-scaling operations, and another performs down-scaling operations. The invention also provides for two-dimensional scaling by selecting horizontal and vertical scaling parameters and generating first and second combined matrices responsive to the parameters and combining them into a single combined matrix. The invention may also incorporate a predetermined cost function.

Abstract: A one-dimensional algorithm for perform the merging of complementary portions from two independent overlapped images on the same 8×8 grid without the computational expense of conversion to and from the real domain is extended to a two-dimensional procedure. The merging process is performed exclusively in the frequency domain. The extension to two dimensions is done by shifting and/or merging rows of side-by-side two-dimensional transformed data blocks using the one-dimensional algorithm. Then a vertical shifting and/or merging can be performed on the horizontally shifted and/or merged blocks again using the one-dimensional algorithm with an independent shift/merge parameter.

Abstract: A one-dimensional (1D) Inverse Discrete Cosine Transform (IDCT) is applied to an input two-dimensional (2D) transform block along the axis to be modified. Since the one-dimensional IDCT is not performed on the other axis, each block is left in a one-dimensional transform space (called hybrid space). For a shift (merge), the appropriate “m” elements are picked up from one block and the “8−m” elements are picked up from the other block and are used as input to the one-dimensional forward DCT (FDCT) along that same axis. For two-dimensional shifts or merges, the results of the first one-dimensional IDCT and FDCT can be stored with extra precision to be used as input to a second one-dimensional IDCT and FDCT along the other axis. The execution time worst case conditions are approximately constant for all shift/merger amounts. Taking advantage of fast paths can improve the execution times for typical blocks.

Abstract: A method of transform domain processing of transformed data is applied to image processing in various applications. A one-dimensional algorithm allows for the selection of an arbitrary contiguous eight component DCT sub-block from two adjacent DCT blocks that foregoes the expense of image manipulation in the real domain. Due to the fact that non-zero DCT coefficients are generally sparse, this algorithm lends itself nicely to the development of special cases which are faster than methods in use today. The de-quantization and re-quantization can be combined at execution time with the constants.