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US 6,785,415 B1Granted
Image processing method, an image processing apparatus, and a recording media on which an image processing program is recorded
AssigneeHitachi Medical Corporation
InventorsJun'ichi Taguchi, Kunihiko Kido
Life of this patent
Estimating the term…
Abstract
In an image processing method and in an image processing apparatus, edge and flat zones of an original image are separately recognized, a first nonlinear flattening process effective for the edge zone is executed to obtain first data, and a second nonlinear flattening process effective for the flat zone is executed to obtain second data. An image is rearranged by using the first and second data for the edge and flat zones, respectively. On a computer-readable recording media, there is stored the image processing method in the form of a program code.
Claims16
An image processing method comprising:
- recognizing an input image by separating an edge zone and a flat zone from the input image;
- conducting a first nonlinear flattening process effective for the edge zone for data of the input image to obtain first data;
- conducting a second nonlinear flattening process effective for the flat zone for data of the input image to obtain second data;
- and
- rearranging an image by using the first data for the edge zone and the second data for the flat zone,
- wherein the first nonlinear flattening process includes:
- setting a plurality of directions about a given point of the input image;
- calculating, for each of the plural directions, a change quantity in a data value of data at a point in the direction relative to a data value of data of the given point;
- generating a data change vector including as elements thereof the change quantities in the plural directions;
- setting at each of a plurality of points in the neighborhood of the given point a plurality of directions about the point;
- calculating, for each of the plural directions, a change quantity in a data value of data at a point relative to a data value of data of the point in the neighborhood of the given point;
- generating a data change vector including as elements thereof the change quantities in the plural directions about the point in the neighborhood of the given point;
- adding the data change vector of the given point to the data change vector of the point in the neighborhood of the given point by assigning weight coefficients to each of the vectors and thereby generating a blur data change vector of the given point;
- selecting a direction of an element having a minimum value from the elements of the blur data change vector;
- and
- conducting a one-dimensional nonlinear flattening process in accordance with data of a plurality of points in the direction of the minimum value element selected.
13 more elements
An image processing method, comprising the steps of:
- a) calculating, for each of plural directions about a given point of an original image, a change quantity in a data value of data at a point the direction relative to a data value of data of the given point, and generating a data change vector including as elements thereof the change quantities in the plural directions;
- b) calculating, for each of a plurality of points in the neighborhood of the given point, a change quantity in a data value of data at a point in the direction relative to a data value of data of the point in the neighborhood of the given point, and generating a data change vector including as elements thereof the change quantities in the plural directions about the point in the neighborhood of the given point;
- c) adding the data change vector of the given point to the data change vector of the point in the neighborhood of the given point by assigning weight coefficients to each of the vectors and thereby generating a blur data change vector of the given point;
- d) selecting a direction of an element having a minimum value from the elements of the blur data change vector;
- e) conducting a nonlinear flattening process in accordance with data of a plurality of points in the direction of the minimum value element selected, and generating minimum blur change direction flat image data using data obtained by the nonlinear flattening process;
- f) generating a map for discrimination of an edge zone and a flat zone of the image in accordance with the minimum blur change direction flat image data;
- g) conducting a predetermined second nonlinear flattening process for data of the given point of the original image, and generating flat image data using data obtained by the second nonlinear flattening process;
- and
- h) rearranging an image with reference to the map by using the minimum blur change direction flat image data for the edge zone of the image and the flat image data obtained by the second nonlinear flattening process for the flat zone.
6 more elements
An image processing method in which an input image is recognized by separating an edge zone and a flat zone from the input image, a first nonlinear flattening process is executed on the edge zone of the input image in a predetermined direction, and a second nonlinear flattening process is executed on the flat zone of the input image, wherein the first nonlinear flattening process on the edge zone of the input image comprises:
- calculating a brightness change value for each of plural directions at each point of the input image;
- generating a brightness change vector having a component of the brightness change value;
- generating a blur brightness change vector of a given point by averaging the brightness change vector of the given point and brightness change vectors of neighborhood points of the given point with predetermined weight coefficients;
- determining a minimum blur change direction that is a direction of a minimum value in components of the blur brightness change vector;
- and
- conducting a one-dimensional nonlinear flattening process in accordance with data of a plurality of points in the direction of the minimum blur change direction.
3 more elements
An image processing method comprising the steps of:
- generating a brightness change vector having a component of a brightness change value by calculating the brightness change value for each of predetermined plural directions at each point of an input image;
- generating a blur brightness change vector of a given point by averaging the brightness change vector of the given point and brightness change vectors of neighborhood points of the given point with predetermined weight coefficients;
- determining a minimum blur change direction that is a direction of a minimum value in components of the blur brightness change vector;
- and
- conducting a one-dimensional nonlinear flattening process in accordance with data of a plurality of points in the minimum blur change direction, and generating minimum blur change direction flat image data using data obtained by the one-dimensional nonlinear flattening process;
- generating a map for discrimination of an edge zone and a flat zone of the input image in accordance with the minimum blur change direction flat image data;
- and
- generating an output image with reference to the map by using the minimum blur change direction flat image data for an edge zone of the input image and by using data obtained by a predetermined nonlinear flattening process for a flat zone of the input image.
5 more elements
An image processing apparatus comprising:
- means for recognizing an input image by separating an edge zone and a flat zone of the input image;
- means for executing a first nonlinear flattening process on the edge zone of the input image;
- means for executing a second nonlinear flattening process on the flat zone of the input image;
- and
- means for generating an output image based on results of said means for executing the first nonlinear flattening process on the edge zone and said means for executing the second nonlinear flattening process on the flat zone,
- wherein said means for executing the first nonlinear flattening process on the edge zone calculates a brightness change value for each of plural directions at each point of the input image;
- generates a brightness change vector having a component of the brightness change value;
- generates a blur brightness change vector of a given point by averaging the brightness change vector of the given point and brightness change vectors of neighborhood points of the given point with predetermined weight coefficients;
- determines a minimum blur change direction that is a direction of a minimum value in components of the blur brightness change vector;
- and conducts a one-dimensional nonlinear flattening process in accordance with data of a plurality of points in the minimum blur change direction.
7 more elements
A computer readable medium recording an image processing program executed by a computer for implementing an image processing method, said image processing method comprising:
- recognizing an input image by separating an edge zone and a flat zone of the input image from each other;
- executing a first nonlinear flattening process on an edge zone of the input image;
- executing a second nonlinear flattening process on a flat zone of the input image;
- and
- generating an output image based on results of executing the first nonlinear flattening process on the edge zone and of executing the second nonlinear flattening process on the flat zone,
- wherein the first nonlinear flattening process on the edge zone comprises the steps of:
- calculating a brightness change value for each of plural directions at each point of the input image;
- generating a brightness change vector having a component of the brightness change value;
- generating a blur brightness change vector of a given point by averaging the brightness change vector of the given point and brightness change vectors of neighborhood points of the given point with predetermined weight coefficients;
- determining a minimum blur change direction that is a direction of a minimum value in components of the blur brightness change vector;
- and
- conducting a one-dimensional nonlinear flattening process in accordance with data of a plurality of points in the minimum blur change direction.
9 more elements
Dependencies are inferred from the claim text.