A method of optimizing the optical focus of an electro-optical sensor in preparation for accurately measuring an optical parameter thereof of the type including, but not limited to, dynamic range, modulation transfer function, minimum resolvable temperature difference and field of view, includes changing a focus of the sensor on a target image viewed by the sensor while obtaining successive output images produced by the sensor, constructing respective image vectors from respective ones of the output images, for each one of the image vectors transforming the image vector by transform to produce a transformed image vector of elements whose values correspond to spatial frequency content computing a sum of squares of elements of the transformed image vector to produce a focus metric and identifying the focus of the recorded image corresponding to the greatest focus metric as being the optimum focus.

The invention provides a method and apparatus for enhancing apparent image resolution by way of multi-line interpolation. A method for enhancing the resolution of low-resolution image-data includes the steps of: providing a memory having independently addressable storage banks; storing the low-resolution image-data in the memory such that low-resolution image-data defining a first low-resolution row resides in a first of said storage banks and such that low-resolution image-data defining a second low-resolution row, adjacent to the first low-resolution row, resides in a second of said storage banks; extracting first through Nth low-resolution pixel signals from the memory, said signals representing values of low-resolution pixels in the adjacent first and second low-resolution rows of the low-resolution image-data; and producing a high-resolution pixel signal from said first through Nth low-resolution pixel signals in accordance with a distance-weighted algorithm.

The Invention includes a method and apparatus which analyzes an image of an object to detect and identify defects in the object. The present invention utilizes a scanning technique which converts a 2-D image of the object into a 1-D image, a transformation technique which extracts relevant features from the image, and a fuzzy inferencing technique which utilizes the features generated by the transformation technique to detect and identify defects. The present invention preferably includes an off-line learning process which selects the optimum transform coefficients for a given set of defects and stores the corresponding features in a rulebase. Preferably, the wavelet transform is used as the transformation technique to provide an analysis of the image which is localized in the frequency and time domains. The present invention may also include an on-line learning process when the present invention is incorporated into a manufacturing process for real time inspection of the object being manufactured. The on-line learning process attempts to nullify the effects of noise which may be associated with the image sensors being used to read the image by using a similarity function to maintain a predetermined level of fuzziness of the inference engine of the present invention.

An apparatus produces an encoded and compressed digital data stream from an original input digital data stream using a forward discrete wavelet transform and a tree encoding method. The input digital data stream may be a stream of video image data values in digital form. The apparatus is also capable of producing a decoded and decompressed digital data stream closely resembling the originally input digital data stream from an encoded and compressed digital data stream using a corresponding tree decoding method and a corresponding inverse discrete wavelet transform. A dual convolver is disclosed which performs both boundary and nonboundary filtering for forward transform discrete wavelet processing and which also performs filtering of corresponding inverse transform discrete wavelet processes. A portion of the dual convolver is also usable to filter an incoming stream of digital video image data values before forward discrete wavelet processing. Methods and structures for generating the addresses to read/write data values from/to memory as well as for reducing the total amount of memory necessary to store data values are also disclosed.

A compression and decompression method using a wavelet decomposition, frequency based tree encoding, tree based motion encoding, frequency weighted quantization, Huffman encoding, and tree based activity estimation for bit rate control. Forward and inverse quasi-perfect reconstruction transforms are used to generate the wavelet decomposition and to reconstruct data values close to the original data values. The forward and inverse quasi-perfect reconstruction transforms utilize special filters at the boundaries of the data being transformed and/or inverse transformed.