Equal sidelobe level on the radiation pattern of the linear array antenna a method is described for obtaining an equal sidelobe level in the radiation pattern of a linear array by using digitally controlled attenuators rather than the digital phase shifters normally used to control the amplitude of the current. It controls the peak level of the sidelobed and the level in arbitrary directions in the radiation pattern at the same time. Simulation showed that the attenuators can be changed in steps of 0.03dB or less, so the quantisation error has less effect on the radiation pattern than do phase shifters. They are also less expensive.
An all-format decoder (AFD), which is an MPEG-2 MP@HL video decoder, has been developed for digital television. It uses a media accelerated processor for consumer appliances 2000 (MAPCA2000), which is based on the very-long-instruction-word architecture. The AFD decodes an MPEG-2 video stream using some of the discrete cosine transform coefficients in the input stream. The algorithm it uses to decode the stream reduces the amount of memory and processor power required. By efficiently using single-instruction multiple-data instructions, a direct-memory-access engine, and a co-processor for variable-length decoding, the AFD can decode 1080i-format video streams in real time using a standard MAPCA2000 running on a 300-MHz CPU with a 100-MHz external-memory bus clock and only 3.5 MB of external memory.
A technique is described for restoring digital images using an innovative spatially variant inverse filter that corrects for the image blurring caused when the point spread function (PSF) of a real imaging system with a lens changes its size or shape. The PSFs are estimated for each small local area using a recursive method, and an inverse filter is constructed for each area. The cost function for determining the PSFs is a function of the thickness of the phase-only-synthesis image-edge line. To obtain high-quality images, a new image sharpening technique is applied to the restored images. To reduce noise in the images, the perturbation method is introduced in our work. Simulation showed that this technique restores digital images better than conventional techniques.
An approach is described for classifying images that does not require first dividing an image into small blocks and then classifying it based on the features of the individual blocks, as do traditional approaches. Instead the line features of the entire image are extracted and used, along with the pixel intensity, to classify each pixel in the image. To increase the classification speed, a fast line-extraction algorithm has been developed that extracts the line features directly from the original image without pre-processing. A classification tree with single variable splits is used to classify the image. Testing of a five-class aerial-image classification algorithm showed that it had an average error rate of 17.6%. Running on a 600-MHz Pentium III processor, it had an average classification time of 2.18 seconds for 512×512 grayscale images. This approach can be used for many different applications by training the classification tree with the desired classes.
A method is described for searching for videos similar to a query. The video frames are segmented into shots by clustering consecutive frames based on their color histograms. Segmentation performance is improved by adding temporal information to the color data. Videos are represented by their temporal distribution of the colors, and the distance between videos is estimated based on the effort needed to transform one distribution into another. The distance is used to search videos similar to a query. The search is speeded up by using a filtering method based on the inequalities in distances. Testing of the method showed that the performance of the similarity search is improved by incorporating the temporal information.