Oriented filters are useful in many early vision and image processing tasks. One often needs to apply the same filter, rotated to different angles under adaptive control, or wishes to calculate the filter response at various orientations. We present an efficient architecture to synthesize filters of arbitrary orientations from linear combinations of basis filters, allowing one to adaptively "steer" a filter to any orientation, and to determine analytically the filter output as a function of orientation.

In this paper, we present a perceptual distortion measure that predicts image integrity far better than meansquared error. This perceptual distortion measure is based on a model of human visual processing that ts empirical measurements of the psychophysics of spatial pattern detection. The model of human visual processing proposed involves two major components: a steerable pyramid transform and contrast normalization. We also illustrate the usefulness of the model in predicting perceptual distortion in real images. 1.

this paper, the boxes H i #!# indicate circular convolution of a #nite input image of size N with a #lter with impulse response h i #n# and Fourier transform

Two paradigms for visual analysis are top-down, starting from high-level models or information about the image, and bottom-up, where little is assumed about the image or objects in it. We explore a local, bottom-up approach to image analysis. We develop operators to identify and classify image junctions, whichcontain important visual cues for identifying occlusion, transparency, and surface bends. Like the human visual system, we begin with the application of linear filters which are oriented in all possible directions. Wedevelop an efficientway to create an oriented filter of arbitrary orientation by describing it as a linear combination of basis filters. This approach to oriented filtering, which we call steerable filters, offers advantages for analysis as well as computation. We design a variety of steerable filters, including steerable quadrature pairs, which measure local energy. We show applications of these filters in orientation and texture analysis, and image representation and enhanc...

This research investigates the use of pyramid coding in various digital image and video compression applications, the progressive transmission of images, and the efficient ecovery of motion information from video sequences. Through the use of feedback, pyramid coding allows both flexibility in th choice of filters, and the use of quantization noise feedback. While the filters have a significant effect on the properties of the generated pyramid, quantization feedbackallows more control over the distortion introduced indirectly into the reconstructed image through separate quantization of the pyramid subimages. After a frequency domain analysis of pyramid coding, a new class of decimation and interpolation filters is developed. The use of both different filters, and quantization feedback in various applications is then explored. This is followed by proposals regarding possible choices of generation schemes and filters for the efficient implementation of pyramid coding in these applications. Finally, the performance of the pyramid codec is evaluated against both optimal methods, where appropriate, and other proposed suboptimal methods. For example, a filter pair is proposed for lossless image coding that not only leads to the generation of low entropy pyramids, but also allows a given image to be represented as a subsampled pyramid of the same number of pixels. Lossless compression ratios significantly higher than in the case of related techniques are achieved by this form of pyramid coding, while generally at a fraction of the computational cost. Appropriate filters are also proposed for the generation of pyramids suitable for the recovery of motion information from video sequences. Using hierarchical motion field recovery, based on pyramids generated with these filters, it i...