Image analysis – Image compression or coding – Substantial processing of image in compressed form
Reexamination Certificate
2000-05-08
2003-06-24
Mehta, Bhavesh M. (Department: 2625)
Image analysis
Image compression or coding
Substantial processing of image in compressed form
C382S250000, C382S280000, C358S001900, C358S003060
Reexamination Certificate
active
06584225
ABSTRACT:
FIELD OF THE INVENTION
This invention relates to the field of image processing. In particular, this invention is drawn to digital halftoning and image compression.
BACKGROUND OF THE INVENTION
The process of digitizing a spatial representation of a source image or manipulating the digital data corresponding to the source image is frequently referred to as digital image processing. A continuous tone source image can be digitized by quantifying discrete regions of the image (i.e., pixels) into a range of finite, discrete values that can be represented digitally (pixel values). In digital form, the source image may be easily copied and distributed. The digital representation of the spatial image can then be used to reconstruct the source image. Differences between the source image and the reconstructed image result at least in part from the quantification of analog values. Reduction of the spatial image information through a compression process may result in the introduction of additional artifacts into the reconstructed image.
Techniques such as halftoning or dithering may be used to ameliorate the perceived effect of quantification and compression in image reproduction. These techniques rely on the tendency of the human eye to average or blend the discrete units.
In an image processing pipeline, spatial quantization, compression, and halftoning are serially performed steps. Spatial quantization and halftoning are performed in the spatial domain. Compression typically takes place in the frequency domain. Transforming from one domain to another and then back again is computationally expensive. Moreover, the serial performance of these steps undesirably increases the length of the image processing pipeline.
SUMMARY OF THE INVENTION
In view of limitations of known systems and methods, a method of processing an image includes the step of transforming spatial image data to generate a first set of frequency domain basis coefficients. The first set of basis coefficients are combined with a second set of basis coefficients corresponding to a frequency domain transform of a pre-determined halftone texture. In various embodiments, the forward transform is a selected one of the discrete cosine transform, the discrete sine transform, and the Fourier transform. The combined basis coefficients are quantized and entropy encoded to generate the compressed image data. After any necessary decompression, an inverse transform may be subsequently performed to reconstruct the source spatial image with the pre-determined halftone texture.
In one embodiment, a method of processing a source image includes the step of scanning the source image to generate digitized spatial image data. The digitized data is subdivided into a plurality of blocks. A forward transform is applied to each block to generate source image basis coefficients. The source image basis coefficients are then combined with halftone basis coefficients corresponding to a pre-determined halftone texture. The combined basis coefficients may be quantized and entropy encoded to generate the compressed image data. After decompression, the spatial image reconstructed through inverse transformation incorporates the pre-determined halftone texture.
Other features and advantages of the present invention will be apparent from the accompanying drawings and from the detailed description that follows below.
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Gonzalez et al, Digital Image Processing, 1992, Addison-Wesley Publishing Co, Inc, p 663-667.*
J S Chen, A comparative study of digital halftoning techniques, Prceedings of the IEEE 1992 National Aerospace and Electronics Conference, May 18-22 1992, vol. 3, p 1139-1145.
Hewlett--Packard Development Company, L.P.
Mehta Bhavesh M.
Sukhaphadhana Christopher
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