Proposals:Consistent usage of label and binary images: Difference between revisions
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A binary image is an image containing a background and a foreground. It is perfectly possible to represent it with a bool as pixel type, however, most of the time, we will prefer an integral type such as unsigned char. Unsigned char type has an important advantage over the bool type: it allows to have several objects with different pixel values, or labels. | A binary image is an image containing a background and a foreground. It is perfectly possible to represent it with a bool as pixel type, however, most of the time, we will prefer an integral type such as unsigned char. Unsigned char type has an important advantage over the bool type: it allows to have several objects with different pixel values, or labels. | ||
The notion of binary image and label image are closely related, but are different. It must be clearly defined | The notion of binary image and label image are closely related, but are different. It must be clearly defined the wich one is used in a class. | ||
==Definitions== | ==Definitions== | ||
Both binary and label images have integral pixel type. | |||
===Binary image=== | ===Binary image=== | ||
A binary image is defined by a single foreground value | |||
A binary image is defined by a single foreground value, y default, the maximum possible value of the pixel type . The other values found in the image are in the background of the image. With that definition, the user can easily manipulate each object in the image individually. Example of usage: dilate only one object in a labeled image. Example: a mask is a binary image, not a label image. | |||
===Label image=== | ===Label image=== | ||
A label image is defined by a single background value, the minimum pixel value of the type, or even no background. The other values found in the images are the labels. With that definition, the user can easily manipulate all the objects of an image. Example of usage: give some markers to perform a watershed (a background is needed). Other example: give a label to all the pixels of the images, with a classification algorithm for example (a background is not needed) | |||
A label image is defined by a single background value, by default, the minimum pixel value of the type, or even no background. The other values found in the images are the labels. With that definition, the user can easily manipulate all the objects of an image. Example of usage: give some markers to perform a watershed (a background is needed). Other example: give a label to all the pixels of the images, with a classification algorithm for example (a background is not needed). | |||
==Naming covention== | |||
A filter which manipulate binary images should be prefixed with Binary if it manipulates binary images, or with Label if it manipulates label images. | |||
For example, an filter wich filter all the objects smaller than a given size in a binary image (a classical binary area opening) should be called BinaryAreaOpeningImageFilter; a filter which filter all the objects smaller than a given size in a label image should be called LabelAreaOpeningImageFilter. Note that the 2 filters would not perform the same operation: BinaryAreaOpeningImageFilter first has to found the connected components, and then perform the area opening, while LabelAreaOpeningImageFilter would consider each pixel with the same value as a single object, and so wouldn't have to search the connected components. | |||
==Boolean operations== | |||
==Backward compatibility== | |||
Revision as of 15:26, 11 October 2006
Summary
Currently, a label image or a binary image can be different things in the toolkit. This proposal give some clear and consistant definition of a label and a binary image, and a way to use them without breaking (immediately) the backward compatibility.
Background
Label images and binary images are not consistently defined in the toolkit currently: the definition is dependent of the the class which manipulate the image. For example, ConnectedComponentImageFilter consider that binary objects are connected set of non-zero pixels, while BinaryDilateImageFilter use a value setted by the user to manipulate the binary object. Also, while we can consider as label any value allowed by a type, some filters may fail if those values are negative. It clearly increase the complexity of the toolkit, and sometime makes the behavior of such ar such class difficult to understand.
A binary image is an image containing a background and a foreground. It is perfectly possible to represent it with a bool as pixel type, however, most of the time, we will prefer an integral type such as unsigned char. Unsigned char type has an important advantage over the bool type: it allows to have several objects with different pixel values, or labels.
The notion of binary image and label image are closely related, but are different. It must be clearly defined the wich one is used in a class.
Definitions
Both binary and label images have integral pixel type.
Binary image
A binary image is defined by a single foreground value, y default, the maximum possible value of the pixel type . The other values found in the image are in the background of the image. With that definition, the user can easily manipulate each object in the image individually. Example of usage: dilate only one object in a labeled image. Example: a mask is a binary image, not a label image.
Label image
A label image is defined by a single background value, by default, the minimum pixel value of the type, or even no background. The other values found in the images are the labels. With that definition, the user can easily manipulate all the objects of an image. Example of usage: give some markers to perform a watershed (a background is needed). Other example: give a label to all the pixels of the images, with a classification algorithm for example (a background is not needed).
Naming covention
A filter which manipulate binary images should be prefixed with Binary if it manipulates binary images, or with Label if it manipulates label images.
For example, an filter wich filter all the objects smaller than a given size in a binary image (a classical binary area opening) should be called BinaryAreaOpeningImageFilter; a filter which filter all the objects smaller than a given size in a label image should be called LabelAreaOpeningImageFilter. Note that the 2 filters would not perform the same operation: BinaryAreaOpeningImageFilter first has to found the connected components, and then perform the area opening, while LabelAreaOpeningImageFilter would consider each pixel with the same value as a single object, and so wouldn't have to search the connected components.
