PANSHARP

Description

PANSHARP creates high-resolution color images by fusing black-and-white panchromatic and multispectral color images. This image fusion technique is known as pansharpening and supports 8-bit, 16-bit, or 32-bit real data types. PANSHARP can fuse images obtained from the same sensor or from different sensors. Although other image fusion techniques such as Intensity, Hue, and Saturation (IHS) and ImageLock Data Fusion can also be used, PANSHARP produces superior sharpening results while preserving the spectral characteristics of the original images.

Parameters

Name	Type	Caption	Length	Value range
FILI *	String	Input file name	1 - 192	1 -
DBIC	Integer	Input multispectral channel	0 -
DBIC_REF	Integer	Input reference image channels	0 -
FILI_PAN *	String	Input panchromatic file name	1 - 192	1 - 1
DBIC_PAN	Integer	Input panchromatic image channel	0 - 1
SRCBGD	String	Source background value	0 - 192	Default: FILE
ENHANCE	String	Enhanced pansharpening option	0 - 3	YES | NO Default: YES
RESAMPLE	String	Resampling method	0 - 5	CUBIC | BILIN Default: CUBIC
FILO *	String	Output file name	1 - 192	1 -
DBOC	Integer	Output channel	0 -
FTYPE	String	Output file type	0 - 4	Default: PIX
FOPTIONS	String	Output file options	0 - 64
POPTION	String	Pyramid options	0 - 32	OFF | NEAREST | AVERAGE | MODE | BILIN | CUBIC Default: AVERAGE
REPORT	String	Report mode	0 - 192	Quick links

* Required parameter

Parameter descriptions

FILI

Specifies the name of the input file containing the low-resolution multispectral (color) data to be fused with the high-resolution panchromatic image data.

DBIC

Specifies the multispectral channel(s) of the input image file. These channels are fused with the high-resolution panchromatic image data. Duplicate channels are not allowed.

Any multispectral channel can be used, including those that are outside of the range specified by DBIC_REF (InputRef). Using the channels specified by DBIC_REF (InputRef) yields more accurate results.

Ranges of channels or segments can be specified with negative values. For example, {1,-4,10} is internally expanded to {1,2,3,4,10}. When you are not specifying a range in this way, only 48 numbers can be specified explicitly.

DBIC_REF

Specifies the reference image channel(s) in the input file. These channels and the channels of the panchromatic image span the same range of frequency (wavelength) response. Duplicate channels are not allowed.

The use of DBIC_REF (InputRef) channels varies from sensor to sensor. For more information, refer to the Details section.

If this parameter is not specified, PANSHARP determines the appropriate reference bands based on the available wavelength information for both FILI_PAN (InputPan) and DBIC (Input). PANSHARP generates a warning if it cannot find any metadata and use all the bands in the input file.

PANSHARP will generate an error if the wavelength is present and there is no overlap.

Ranges of channels or segments can be specified with negative values. For example, {1,-4,10} is internally expanded to {1,2,3,4,10}. When you are not specifying a range in this way, only 48 numbers can be specified explicitly.

FILI_PAN

Specifies the name of the input file that contains the high-resolution panchromatic image data.

DBIC_PAN

Specifies the channel that contains the high-resolution panchromatic image data from FILI_PAN. Only one channel must be specified. By default channel 1 is used.

SRCBGD

Specifies which pixels in the source images are to be considered as background (NoData) pixels. The same rule is applied to both of the input images independently. In general, if a pixel is considered NoData, the application handles the pixel in a special manner.

ENHANCE

Specifies whether to generate a refined pansharpened image. The default value is YES.

RESAMPLE

Specifies the resampling method to use to determine the output pixel values when resampling the input low-resolution data to the higher resolution panchromatic data.

Supported values are:

• CUBIC: cubic convolution; this is the default value.
• BILIN: bilinear interpolation.

Bilinear interpolation is recommended if further analysis (such as classification) using the output is expected, as it will keep the output values closer to the original MS pixel values.

FILO

Specifies the name of the file to receive the output pansharpened multispectral input channels.

If FILO does not exist, it is created with the extents that match the overlap of FILE_PAN and FILI, using the resolution specified in FILE_PAN.

DBOC

Optionally specifies the channel(s) to receive the output pansharpened input channels. If this parameter is not specified, the first N channels are used, where N is the number of selected input channels.

Duplicate channels are not allowed.

Ranges of channels or segments can be specified with negative values. For example, {1,-4,10} is internally expanded to {1,2,3,4,10}. When you are not specifying a range in this way, only 48 numbers can be specified explicitly.

FTYPE

Specifies the output file format type, represented by a three- or four-letter code. The format type must be a GDB-supported file type.

The default value is PIX.

A full list of GDB-recognized file types and their codes is provided in the GDB file formats section of the CATALYST Professional Online Help.

FOPTIONS

Specifies the file creation options to be applied when creating the output file. These are specific to the file format; in each case, the default of no options is allowed. This parameter can be used to specify the compression schemes, file format subtypes, and other information.

Different options are available for different file types (see the FTYPE parameter). The options are described in the GDB file formats section of the CATALYST Professional Online Help.

POPTION

Specifies the resampling method to be used to compute the overview levels. The following options are available:

• OFF: disables the production of overviews. Although this option delays the browsing of an image, it completes the processing task quickly and uses a minimum amount of disk space.
• NEAREST: applies a closest-neighbor resample.
• AVERAGE: calculates the average value of all of the pixels that contribute to the overview pixel. This option is used for continuous-tone images and produces a better looking and more interpretable overview than the NEAREST method; however, this option cannot be used for classified, pseudocolor, or thematic images because it introduces intermediate values not found in the original image. This is the default value.
• MODE: takes the mode of the pixels that contribute to the overview pixel. This method is used for classified, pseudocolor, or thematic images, but is not used for continuous-tone images.
• BILIN: applies a bilinear interpolation.
• CUBIC: applies a cubic-convolution resampling.

Thematic image overviews, such as classification results, must be computed using the MODE method, while continuous-tone images, especially radar images, must be computed using the AVERAGE option. Building overviews using the AVERAGE or MODE options can be significantly slower than computing them using the NEAREST method. If the characteristics of an image are not known, or if the speed of preparing the image overview is important, select the NEAREST option.

REPORT

Specifies where to direct the generated report.

Available options are:

• TERM: generates a report on the terminal (default)
• DISK: generates a report on file "IMPRPT.LST"
• OFF: turns off report generation
• <filename>: appends a report to the specified file

Details

PANSHARP applies the automatic image fusion algorithm to increase the resolution of multispectral (color) image data by using a high resolution black-and-white (panchromatic) image.

The power of PANSHARP lies in the simplicity of its algorithm and its versatility. It works with any image data type (8-bit unsigned, 16-bit signed/unsigned, 32-bit floating point) and is computationally efficient.

For best results, the input reference image channels must be selected in such a way that the multispectral bands cover as closely as possible the frequency range of the high-resolution panchromatic image.

If wavelength information is available for both FILI_PAN and FILI, DBIC_REF should be left empty so that the program can automatically determine the best reference channel selection. Use DBIC_REF to override the automatic reference channel selection mechanism.

The following list shows the reference bands for some well-known satellite sensors:

Landsat 7 (ETM+):     Green:2, Red:3, Near IR:4
SPOT 1, 2, 3 (HRV):   Green:1, Red:2
SPOT 5 (HRG):         Green:1, Red:2
IRS 1C, 1D:           Green:1, Red:2
IKONOS:               Blue:1, Green:2, Red:3, Near IR:4
QUICKBIRD:            Blue:1, Green:2, Red:3, Near IR:4
Worldview-2 (4-band): Blue:1, Green:2, Red:3       
Worldview-2 (8-band): Blue:2, Green:3, Yellow:4, Red:5, Red Edge:6

The channel number given in the table above is the standard ordering on the sensor and may differ from the order in an actual data file.

The order in which the reference input channels are specified is not important.

If FILO does not exist, a new file will be created with georeferenced extents equal to the common bounding box of the panchromatic and multispectral reference channels and pixel size equal to that of the panchromatic image.

If FILO exists, the image within the common bounding box of the panchromatic, multispectral and output channels will be pansharpened and saved to the output file. The sections of panchromatic or multispectral images that are not located within the common bounding box but are within the bounds of the output file, will be interpolated to the output file resolution using cubic convolution and then copied to the output file.

The better the co-registration of the input panchromatic and multispectral image data is, the better the results from this function will be. If a geometric correction pre-processing step can improve this co-registration, then it should be considered.

Atmospheric differences between the times at which the panchromatic and multispectral images are acquired will reduce the quality of the results from this function. Images that have been acquired simultaneously should be used if possible. Landsat 7, IKONOS, Quickbird and the Spot series of satellite-borne sensors deliver simultaneously acquired panchromatic and multispectral image data.

It is recommended that the ratio of ground sample distances between the multispectral and panchromatic images not exceed 5:1. For example, IKONOS data with 4m MS and 1m Pan have a ratio of 4:1, which is acceptable. However, Landsat 7 30m multispectral images have 50 times the ground sample distance of Quickbird 0.61m panchromatic images, and an attempt to sharpen the former with the latter would produce poor results.

The mean, standard deviation, and histogram shape for each multispectral image is typically only slightly modified by sharpening with this function, so long as the ground sample distance ratio guideline described above is followed and the set of reference images closely cover the same wavelength range as the panchromatic image.

If a pixel is NoData in either of the input images, it will be NoData in the output. Regardless of the value of the input NoData, the output NoData value will always be 0.

Example

A QuickBird multispectral image set in a PCIDSK file named toronto_ms_demo.pix will be sharpened using the correpsonding QuickBird panchromatic image in a PCIDSK file named toronto_pan_demo.pix. The sharpened images will be written to a new PCIDSK file called pansharp.pix.

The four multispectral images that are to be sharpened will also be used as the reference images.

EASI>FILI	=	"toronto_ms_demo.pix"
EASI>DBIC	=	1,2,3,4
EASI>DBIC_REF	=	DBIC	! reference images are also 
			! the image to be sharpened
EASI>FILI_PAN	=	"toronto_pan_demo.pix"
EASI>DBIC_PAN	=	1
EASI>SRCBGD	=	"ANY, 0"	! zero-valued pixels in any input image are
			! excluded from processing
EASI>ENHANCE	=	"YES"	! apply the color enhancement operation
EASI>RESAMPLE =      "CUBIC" ! use cubic interpolation when resampling MS image to 
                                ! high resolution
EASI>FILO	=	"pansharp.pix"
EASI>DBOC	=	1,2,3,4
EASI>ftype	=	"TIF"	! the output file will be in GeoTIFF format
EASI>foptions	=	"TILED512"	! output file will be tiled into 
			! 512x512 pixel tiles
EASI>POPTION	=	"AVERAGE"	! unweighted averaging resampling 
			! used to build pyramid overview images
EASI>RUN PANSHARP
            

Algorithm

Based on thorough studies and analyses of existing fusion algorithms and fusion effects, a new automatic fusion approach has been developed. This new approach solved the two major problems: color distortion and operator/data dependency.

An approach based on least squares was developed to best approximate the gray value relationship between the original multispectral, panchromatic and the fused images to achieve a best color representation.

Statistical approaches were developed to realize a standardized and automated fusion process.

How to get the best results

A number of image fusion algorithms have been developed targeting different image sensors or applications. Typical problems found with existing algorithms include: (1) color distortion and (2) operator and data set dependency. Although the image fusion technique implemented in PANSHARP diminishes greatly those deficiencies, no algorithm is known to produce "perfect" results. The pansharpened multispectral images will inherit the level of spatial details from the panchromatic image data but won't benefit from sufficient color information to guarantee "true" high resolution multispectral images. Thus, spatial features of sizes smaller than the multispectral sensor resolution may be assigned "fake" color although visually the image quality appears to be excellent.

Another very important aspect of image fusion algorithms is ensuring very good co-registration of the input panchromatic and multispectral image data. This problem becomes more pronounced with high resolution sensors as IKONOS or Quickbird. A single pixel offset between the high resolution panchromatic image data and the low resolution multispectral image data results in color shifts clearly visible in the pansharpened imagery. Thus, a pre-processing step such as geometric correction or orthorectification, may be required before pansharpening the multispectral image data.

For best results, it is highly desirable that the high resolution panchromatic image data and the low resolution multispectral image data be acquired simultaneously. This will ensure consistency of the spatial and spectral features of the scene. Landsat 7, IKONOS, Quickbird and the Spot series of satellites offer simultaneously acquired imagery.

Due to the lack of sufficient color information in low resolution multispectral imagery, it is recommended that the ratio of resolutions between the images do not exceed 5:1. For example, IKONOS with 4m MS and 1m Pan has a ratio of 4:1 which is acceptable. However, mixing Landsat 7 30m MS with Quickbird 0.61m Pan would have a ratio of about 50:1 and the resulting fused image would have poor color quality.

PANSHARP produces best results for multispectral image channels whose wavelengths lie within the frequency range of the panchromatic image channel. Multispectral channels outside the wavelength range of the high resolution panchromatic image channel will still look good but may have reduced physical meaning.

Spectral characteristic preservation

The PANSHARP algorithm attempts to preserve spectral characteristics (that is, the color of the image). The mean, standard deviation and histogram shape for each channel are approximately preserved. Significant deviations from the original histogram shape can occur, however, if the resolutions of the multispectral and panchromatic imagery differ greatly or if data from different sensors is used together.

For more information and comparative results, see the References section.

Acknowledgements

The automatic image fusion algorithm was developed by Dr. Yun Zhang from the University of New Brunswick.

Dr. Yun Zhang
Department of Geodesy and Geomatics Engineering
University of New Brunswick
Fredericton, New Brunswick
Canada E3B 5A3

References

The following references describe the algorithm that is implemented by this function.

Zhang, Yun. (2002). "Problems in the fusion of commercial high-resolution satellite as well as Landsat 7 images and initial solutions". In ISPRS, Vol. 34, Part 4, GeoSpatial Theory, Processing and Applications, Ottawa, Canada.

Zhang, Yun. (June 24-28, 2002). "A new automatic approach for effectively fusing Landsat 7 as well as IKONOS images". IEEE/IGARSS'02, Toronto, Canada.