Image analysis – Image enhancement or restoration – Image filter
Reexamination Certificate
2000-08-01
2004-03-02
Au, Amelia M. (Department: 2622)
Image analysis
Image enhancement or restoration
Image filter
C382S274000
Reexamination Certificate
active
06701024
ABSTRACT:
BACKGROUND OF THE INVENTION
The present invention relates to an image processing apparatus and, more particularly, to an image processing apparatus for adjusting the spatial frequency characteristics of a two-dimensional image sensed by an electronic camera.
An image sensing apparatus such as an electronic camera (digital still camera) for sensing an image using an image sensor such as a multi-color CCD adjusts the spatial frequency characteristics of an obtained two-dimensional image.
For example, in an image sensing apparatus using a single multi-color filtered CCD, an obtained image is made up of many pixels having luminance values of different color components such as R, G, and B.
Pixels of the same color component are arrayed in a checkered pattern, and the resolution is substantially low in comparison with the number of pixels.
A general electronic camera comprises an image processing apparatus to adjust the spatial frequency characteristics of an input image in order to perform edge enhancement of an input image or another image processing for compensating for low resolution.
As shown in
FIG. 14
, a conventional image processing apparatus
110
adjusts spatial frequency characteristics by software convolution calculation using a DSP (Digital Signal Processor)
120
.
An image signal obtained by an image sensor (CCD)
10
is A/D-converted by a signal converter
11
, and stored as an input image in a memory
12
.
An input image
13
read out from the memory
12
is processed by the DSP
120
for each submatrix of M×M pixels (M is an odd number of 3 or more), and a new luminance value
130
of the central pixel is calculated to obtain an output image
19
whose spatial frequency characteristics are adjusted.
In general, spatial filtering processing for adjusting spatial frequency characteristics must execute, every M×M pixels, so-called product-sum calculation processing of multiplying the luminances of the pixels and predetermined coefficients corresponding to the pixels, and adding the products of all the pixels.
There are proposed a method of preparing a plurality of filter coefficients used to adjust spatial frequency characteristics, and adaptively selecting and using these filter coefficients based on the pixel pattern of a predetermined region (see, e.g., U.S. Pat. No. 5,684,600), and a method of expressing coefficients for a central pixel and its adjacent pixels as a function of a variable k, and selecting k based on the luminance value of the central pixel to adaptively switch the degree of adjustment of spatial frequency characteristics (see, e.g., U.S. Pat. No. 5,854,859).
Since the conventional image apparatus performs product-sum calculation by software, the degree of freedom in adjustment of spatial frequency characteristics is large. However, when the target is a large submatrix, or complicated processing such as adaptive setting of a high-frequency enhancement degree is to be performed, the calculation time increases in accordance with the processing amount and complexity. Moreover, different processes must be done in accordance with predetermined conditions, so the image processing apparatus cannot cope with high-speed, real-time processing.
If spatial frequency characteristics are adjusted by hardware, the image processing apparatus can cope with real-time processing. However, the submatrix is downsized to minimize increases in circuit scale, processing time, and power consumption. This limits the degree of freedom in adjustment of spatial frequency characteristics.
Recently, high-resolution image sensing elements having more than two million pixels are becoming popular. The image processing apparatus has a low-resolution mode using pixels smaller in number than the pixels of the image sensing element in order to increase the number of recordable images. For this reason, the image processing apparatus must process images having a plurality of resolutions. The apparatus must adjust not only the characteristics of an optical system but also spatial frequency characteristics more flexibly.
SUMMARY OF THE INVENTION
The present invention has been made to overcome the conventional drawbacks, and has as its object to provide an image processing apparatus capable of adjusting spatial frequency characteristics at high speed without performing complicated calculation processing.
To achieve the above object, according to the present invention, there is provided an image processing apparatus for calculating a new luminance value of a central pixel to adjust spatial frequency characteristics of an input image, comprising a plurality of subfilters which are arranged in parallel with each other for a plurality of pixel groups each made up of at least one pixel in a submatrix, multiply sums of luminance values of pixels included in corresponding pixel groups by predetermined coefficients corresponding to desired spatial frequency adjustment filter characteristics, and output products for each submatrix made up of M×M (M is an odd number of not less than 3) pixels centered on pixels constituting an input image for a two-dimensional input image made up of many pixels that are arrayed in a matrix and represent luminance values at positions, totalization means for totaling outputs from the subfilters and outputting a sum as an adjustment amount of the spatial frequency characteristics, and addition means for adding the adjustment amount obtained by the totalization means to an original luminance value of the central pixel and outputting a sum as a new luminance value of the central pixel for each matrix.
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Oh et al., “Cascade/Parallel Form FIR Filters With Powers-of-Two Coefficients,” Circuits and Sysems, 1994, ISCAS '94., 1994. IEEE International Symposium on London, UK May 30-Jun. 2, 1994, New York, NY, USA IEEE, US, pp 545-548 XP010143079, ISBN: 0-7803-1915-X, p. 545, col. 1, Para. 1.
Allen Kenneth R.
Au Amelia M.
LaRose Colin
NuCore Technology Inc.
Townsend and Townsend / and Crew LLP
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