Polaroid Corporation

Imaging Devices, Inc.

Munib A Wober

Michael L Reisch

Ibrahim Hajjahmad

Yibing Yang

Lon E Sunshine

F Richard Soini

F Richard Cottrell

James R Toker

William D Washkurak

Jinjou Lin

Thomas E Haw

Jeannie E Williams

An imaging processor microcircuit incorporating an integral image buffer, preferably a synchronous random-access memory device. Access to the image buffer is controlled by an image buffer access prioritizer. When the prioritizer detects that a device desires image buffer access, it signals all lower-priority devices to suspend accesses until the higher-priority device has completed access. An image sensor interface transfers image sensor data to the image buffer. As each pixel data is read, it is modified by reference data read from the image buffer then stored in the image buffer. The read, modify, write process takes three of a possible five cycles, leaving two unused cycles for image buffer access by other devices. The image buffer is also temporary image storage for an optional LCD and an optional print engine. The LCD interface uses the unused cycles to read LCD image data.

Image processor with integral image buffer

Disclosed herein are a method, apparatus and computer usable medium for linear filtering with filters of any desired shape and length using the wavelet transform as the computation engine by modifying the basis functions. Specifically, the method and apparatus modifies the basis function of the wavelet and/or inverse wavelet transform(s) by convolving it with the desired filter, thereby forming a modified wavelet and/or inverse wavelet transform(s). The linear filtering is performed in the signal processing and image processing related fields using the wavelet transform with a method that is mathematically equivalent to the filtering operation in the spatial domain. Linear filtering in the wavelet based domain eliminates the need for another program for software support or additional silicon area or real estate to accommodate more functions in hardware. The modified wavelet and/or inverse wavelet transform harnesses and leverages the wavelet and/or inverse wavelet basis function of the wavelet and/or inverse wavelet transform so as to perform the desired linear filtering of the digital or analog signals, without incurring extra cost in terms of software computations or hardware modifications.

Method and apparatus for performing linear filtering in wavelet based domain

In order to prevent or minimize blocking artifacts from appearing in an image due to independent processing of each overlapped block of an image by one of many different filters, true pixel correction values are calculated, then added to each pixel of the image so that the transition between adjacent blocks of pixels will be smooth. This corrective method coined 'stitching' is applied in either the spatial or the frequency domain to each block of filtered pixels in the image and generally includes the steps of:

Minimizing blocking artifacts in a filtered image

A method and apparatus are disclosed for converting frequency-coefficient matrices between a configuration in which the matrices are transforms of unoverlapped image-data matrices and a configuration in which the matrices are transforms of overlapped image-data matrices, the image-data matrices comprising image-data terms corresponding to pixels from an original image, the method comprising the steps of: deriving a conversion matrix; transposing the conversion matrix; matrix multiplying a first frequency-coefficient matrix of one configuration by the conversion matrix; matrix multiplying a second frequency-coefficient matrix of the same configuration by the transpose conversion matrix; and combining the product results to form a matrix formatted in the other configuration.

Method and apparatus for conversion of frequency-coefficient matrices

A method or system for structuring an image which corresponds to an original array of pixels, as a forward discrete even cosine transform (DCT) pyramid having a predetermined number of levels where each level is associated with a different DCT frequency band, includes, respectively, the steps or functionality of: partitioning the original array into blocks of overlapped pixels; taking a DCT of each block of overlapped pixels to generate blocks of first level DCT coefficients forming a first level of the DCT pyramid; storing the first level of the DCT pyramid; selecting and storing at least one of the first level DCT coefficients of each block of first level DCT coefficients into a first temporary array; partitioning the first temporary array into blocks of overlapped coefficients; and taking a DCT of each block of overlapped coefficients of the first temporary array to generate blocks of second level DCT coefficients forming a second level of the DCT pyramid. Additional levels can be created by repeating the previous steps, and the processed image can be restored by reversing the above sequence of steps using inverse discrete even cosine transforms.

Structuring a digital image into a DCT pyramid image representation

A method for adjusting the luminance IM.sub.HI of pixels in a high resolution image includes first forming a low resolution image of the original by grouping pixels into superpixels such as 8.times.8 blocks. A low resolution luminance correction value .delta..sub.LO is determined for each superpixel by comparing the luminance of the superpixel to both a predetermined darkness threshold T.sub.D and a predetermined brightness threshold T.sub.B. The low resolution luminance correction value .delta..sub.LO is modified to yield .delta.'.sub.LO for each superpixel by forming islands of the superpixels and smoothing .delta..sub.LO between superpixels within each island. Finally, a high resolution luminance correction value .delta..sub.HI is calculated for each pixel of the original high resolution image by comparing the luminance IM.sub.HI of each pixel to both T.sub.D and T.sub.B, keeping in mind that .delta..sub.HI is generated through a series of mathematical computations as a function of both the pixel luminance IM.sub.HI and the low resolution luminance correction value .delta..sub.LO. Each pixel of the original image is adjusted by the corresponding high resolution luminance correction value .delta..sub.HI and a luminance adjusted image is produced.

Method and apparatus for pixel level luminance adjustment

An image processing system for sample rate conversion of an image signal representing an image of pixels from a first sample rate to a second sample rate includes: an image acquisition device for acquiring the image signal from an image signal source at the first sample rate; a first memory for buffering the input signal; a second memory for storing predetermined discrete cosine transform coefficients; a dot product multiplier for multiplying the image signal retrieved from the first memory times the predetermined coefficients to produce an output signal at the second sampling rate; a third memory for buffering the output signal; control sequencer logic for controlling operation of the image processing system; and an output device for providing a resampled image at the second sampling rate from the output signal. The image processing system facilitates sample rate conversion by segmenting the image into segments of image data points wherein a separate and different offset is determined for each segment. A discrete cosine transform is performed on each segment of image data points to generate corresponding DCT coefficients. Thereafter, resampled image data points are generated by taking a modified IDCT of the DCT coefficients using a modified IDCT basis matrix which is dependent upon a sampling rate conversion ratio and/or an offset.

System and method for sample rate conversion of an image using discrete

A method and system for filtering a digital image with a filter larger than the hardware capabilities of the imaging system is workable by subdividing the large filter into a number of small filters which can each be individually processed by the system. The method includes the steps of: segmenting the digital image into data blocks of a predetermined size; overlapping adjacent data blocks by a predetermined number of pixels; providing a preselected filter kernel; generating small filters by processing a preselected group of components of the filter kernel; applying each of the small filters to each overlapped data block to produce component data blocks; and merging and saving the component data blocks into filtered data blocks according to a predetermined specific criteria, whereby the filtered data blocks represent the filtered digital image.

Large kernel filtering using a fixed-size block processor

Full color resolution of an image is realized by reconstructing an array of image data points from an image signal representing the image into a shifted array of pseudo pixels. The particular grid type of the array will dictate whether color recovery uses only vertical resolution, only horizontal resolution, vertical resolution followed by horizontal resolution, or horizontal resolution followed by vertical resolution. For each color channel, interpolation of missing color components is accomplished by first, taking a DCT of the image data points, then taking a modified IDCT of the DCT coefficients.

System and method for color recovery using discrete cosine transforms

Image processing methods and apparatus by which images in the spatial domain can be represented in the frequency domain through the use of discrete cosine transforms, conveniently operated on to achieve scaling and filtering effects while in the frequency domain, and then retransformed to the spatial domain or stored, displayed, reproduced or transmitted to distant locations for subsequent reuse. The scaling techniques which the invention utilizes can be for image enlargement by interpolation or image reduction by decimation. In the case of decimation, a filtering operation preferably is first performed in the frequency domain to avoid artifacts in the decimation process. The filtering operation is mathematically equivalent to a linear convolution in the spatial domain as a consequence of the properties of the DCT transformation. In both interpolation and decimation procedures, use is made of a hybrid inverse discrete cosine transform in which the series of cosine terms are evaluated at values arrived at by scaling ratio considerations, rather than the usual sampling index increments. As a consequence, image data points other than original image data in the spatial domain can be created or replaced by an approximation technique which involves transforming the image data points to frequency space by a series of terms that can be considered to be continuous over the range of the sampling index corresponding to the original image data.

Coding method and apparatus for resampling and filtering images using

A method and apparatus for applying an image filter to an image signal where image data terms, corresponding to the image signal, are converted by means of an overlapping operation and a scaled forward orthogonal transformation to form frequency coefficient matrices, the image filter is converted by means of a descaled orthogonal transformation to form a descaled frequency filter matrix, and the frequency coefficient matrices are multiplied by the descaled frequency filter matrix to form filtered coefficient matrices for conversion into a filtered image signal by means of an inverse orthogonal transformation process.

Method and apparatus for fast two-dimensional cosine transform filtering

The invention relates to a novel process and system for removing noise from an image by first noise modeling an image signal source to generate noise masks and LUT values characteristic of noise at different frequency levels for each channel, and then applying the stored noise masks and LUT values to an image signal for noise removal. The image is first captured as an electronic image signal by the image signal source, then represented by a pyramid structure whereby each successive level of the pyramid is constructed from DC values of the previous level, and each level of the pyramid corresponds to a different frequency band of the image signal. A Wiener variant filter using DCT transforms is used to filter DCT coefficients at each level. The image is restored with reduced noise by replacing DC values with next level IDCT coefficients then performing an IDCT on the results.

Image noise reduction system using a wiener variant filter in a pyramid

The image processing system of the present invention provides electronic edge detection in keeping with ISO/JPEG/MPEG international compression standards for electronic imaging. Specifically, a novel electronic image processing system for edge detection includes: an image acquisition device for acquiring and representing an image as an electronic image signal; a video memory for storing the image signal; a display for displaying the image signal; a raster to block converter for converting the image signal into block format; a DCT/IDCT processor for transforming the converted signal in accordance with predetermined basis matrices stored in a basis matrix memory; a mask multiplier for generating a mask multiplied signal in accordance with predetermined Laplacian matrices stored in an A matrix memory; a buffer for storing the mask multiplied signal; and a controller for controlling the image processing system in accordance with instructions from a central processing unit (CPU).

System and method for image edge detection using discrete cosine

Image coding methods and apparatus employing discrete cosine transforms for supressing and/or reducing blocking artifacts using a JPEG file format. The methods can be implemented on JPEG hardware slightly modified to provide access to discrete cosine transform coefficients. Filtering techniques by which an overlap procedure for implementing the inventive methods are also disclosed.

Image coding by use of discrete cosine transforms

A method for processing color mapping data includes the steps of performing a discrete cosine transform on color descriptors resulting in a set of corresponding discrete cosine transform (DCT) coefficients. Selected discrete cosine transform coefficients are set to zero in order to produce a revised set of coefficients including a compressed smaller set of coefficients. The smaller set is more readily manipulated and facilitates interpolation. In one embodiment an inverse DCT is performed on the revised set of coefficients to produce a revised map in color space including a revised set of corresponding device dependent color descriptors. Discrete standard color descriptors are interpolated in the revised map by linear interpolation. In another embodiment of the invention, interpolation is included within an inverse cosine continuous transform (ICCT) of the revised set of coefficients employing an ICCT interpolator. Apparatus for implementing the process includes, for example, a computer, an application specific integrated circuit or a digital signal processor.

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Haverhill, MA, United States of America

Munib A Wober