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image - 如何将 TVIPS 摄像头的 tif 校准导入 DM

问题描述

我目前正在使用带有软件 EM-menu 的 TVIPS 相机来获取 TEM 图像。当我使用 DigitalMicrograph (DM) 分析数据（TIF 文件）时，出现了一些问题，因为 DM 无法进行校准。我知道之前已经回答了一个类似的问题：如何将 tif 校准导入 DM。但是TIF文件的标定是存储在X Resolution和Y Resolution（Rational类型，数值相同）中，与FEI和Zeiss不同。我试图修改如何将 tif 校准导入 DM中的代码，但我得到的是 X 分辨率和 Y 分辨率的偏移量，而不是实际值。我不熟悉如何将 TIF 文件中特定偏移量的值（在这种情况下，X 分辨率的偏移量为 82110，Y 分辨率的偏移量为 82118）分配给 DM。下面是我根据提到的问题修改的代码。任何建议都非常感谢。提供了原始 TIF 文件以帮助解决该问题。

// Auxilliary method for stream-reading of values
// BmyGuest's March 10, 2016 code modified to read FEI TEM TIF
// Import and calibrate TVIPS Tiff images
number ReadValueOfType(object fStream, string type, number byteOrder)
{
    number val = 0
    TagGroup tg = NewTagGroup()
    if ( type == "bool" )
    {
        tg.TagGroupSetTagAsBoolean( type, 0 )
        tg.TagGroupReadTagDataFromStream( type, fstream, byteOrder ) 
        tg.TagGroupGetTagAsBoolean( type, val )
    }
    else if ( type == "uint16" )
    {
        tg.TagGroupSetTagAsUInt16( type, 0 )
        tg.TagGroupReadTagDataFromStream( type, fstream, byteOrder ) 
        tg.TagGroupGetTagAsUInt16( type, val )
    }
    else if ( type == "uint32" )
    {
        tg.TagGroupSetTagAsUInt32( type, 0 )
        tg.TagGroupReadTagDataFromStream( type, fstream, byteOrder ) 
        tg.TagGroupGetTagAsUInt32( type, val )
    }
    else Throw("Invalid read-type:"+type)
    return val
}

string ExtractTextFromTiff( string path )
{
    string txt
    if ( !DoesFileExist(path) ) 
        Throw("File not found.\n"+path)

    // Open Stream 
    number fileID = OpenFileForReading( path )
    object fStream = NewStreamFromFileReference(fileID,1)

    // Read data byte order. (1 = big Endian, 2= little Endian for Gatan)
    number val
    number byteOrder = 0
    val = fStream.ReadValueOfType( "uint16", byteOrder )
    byteOrder = ( 0x4949 == val  ) ? 2 : ( 0x4D4D == val ? 1 : 0 )
    //Result("\n TIFF endian:"+byteOrder)

    // Verify TIFF image
    val = fStream.ReadValueOfType( "uint16", byteOrder )
    if ( val != 42 ) Throw( "Not a valid TIFF image" )

    // Browse all directories
    number offset = fStream.ReadValueOfType( "uint32", byteOrder )

    while( 0 != offset )
    {
        fStream.StreamSetPos( 0, offset ) // Start of IFD
        number nEntries = fStream.ReadValueOfType( "uint16", byteOrder )
        for ( number e=0;e<nEntries;e++)
        {
            number tag        = fStream.ReadValueOfType( "uint16", byteOrder )
            number typ        = fStream.ReadValueOfType( "uint16", byteOrder )
            number count      = fStream.ReadValueOfType( "uint32", byteOrder )
            number dataOffset = fStream.ReadValueOfType( "uint32", byteOrder )
            Result("\n entry # "+e+": ID["+tag+"]\ttyp="+typ+"\tcount="+count+"\t offset @ "+dataOffset)
            if ( 5 == typ ) // Rational
            {
                number currentPos = fStream.StreamGetPos()
                fStream.StreamSetPos( 0, dataOffset )
                string textField = fStream.StreamReadAsText( 0, count )
                txt+=textField
                fStream.StreamSetPos( 0, currentPos )
            }   
        }
        offset = fStream.ReadValueOfType( "uint32", byteOrder ) // this is 0000 for the last directory according to spec
    }

    return txt
}

String TruncWhiteSpaceBeforeAndAfter( string input )
{
    string work = input
    if ( len(work) == 0 ) return ""
    while ( " " == left(work,1) )
    {
        work = right( work, len(work) - 1 )
        if ( len(work) == 0 ) return "" 
    }
    while ( " " == right(work,1) )
    {
        work = left( work, len(work) - 1 )
        if ( len(work) == 0 ) return "" 
    }
    return work
}


// INPUT:  String with line-wise information
// OUTPUT: TagGroup
// Assumptions:  
//  - Groups are specified in a line in the format:             [GroupName]
//  - The string contains information line-wise in the format:  KeyName=Vale
TagGroup CreateTagsFromString( string input )
{
    TagGroup tg = NewTagGroup()
    string work = input

    string eoL          = "\n"
    string GroupLeadIn  = "["
    string GroupLeadOut = "]"
    string keyToValueSep= "="
    string groupName = ""

    number pos = find(work,eoL )
    while( -1 != pos )
    {
        string line = left(work,pos)
        work = right(work,len(work)-pos-len(eoL))
        number leadIn  = find(line,GroupLeadIn)
        number leadOut = find(line,GroupLeadOut)
        number sep = find(line,keyToValueSep)
        if ( ( -1 < leadIn ) && ( -1 < leadOut ) && ( leadIn < leadOut ) ) // Is it a new group? "[GROUPNAME]"
        {
            groupName = mid(line,leadIn+len(GroupLeadIn),leadOut-leadIn-len(GroupLeadOut))
            groupName = TruncWhiteSpaceBeforeAndAfter(groupName)
        }
        else if( -1 < sep )                                                 // Is it a value? "KEY=VALUE" ?
        {
            string key  = left(line,sep)
            string value= right(line,len(line)-sep-len(keyToValueSep))
            key   = TruncWhiteSpaceBeforeAndAfter(key)
            value = TruncWhiteSpaceBeforeAndAfter(value)
            string tagPath = groupName + ( "" == groupName ? "" : ":" ) + key
            tg.TagGroupSetTagAsString( tagPath, value )
        }
        pos = find(work,eoL)        
    }
    return tg
}

void ImportTIFFWithTags()
{
    string path = GetApplicationDirectory("open_save",0)
    if (!OpenDialog(NULL,"Select TIFF file",path, path)) exit(0)

    string extractedText = ExtractTextFromTiff(path)
    /*
    if ( TwoButtonDialog("Show extracted text?","Yes","No") )
        result(extractedtext)
    */

    tagGroup infoAsTags = CreateTagsFromString(extractedText )
    /*
    if ( TwoButtonDialog("Output tagstructure?","Yes","No") )
        infoAsTags.TagGroupOpenBrowserWindow(path,0)
    */
result(extractedtext)
//result(infoAsTags) 
// infoAsTags is blank. ZZ
    // Import data and add info-tags
    image imported := OpenImage(path)
    imported.ImageGetTagGroup().TagGroupSetTagAsTagGroup("TIFF Tags",infoAsTags)
    imported.ShowImage()

    // Calibrate image, if info is found
    // It seems FEI stores this value as [m] in the tags PixelHeight and PixelWidth
    // while ZEISS images contain the size of the FOV in the tags "Height" and "Width" as string including unit
    number scaleX = 0
    number scaleY = 0
    string unitX 
    string unitY
    string scaletemp
    number scalestart, scaleend
    string hStr
    string wStr
    if ( imported.GetNumberNote("TIFF Tags:XResolution", scaleX ) )
    {
        unitX = "nm"
        scaleX = 1e7/scaleX
    }
    if ( imported.GetNumberNote("TIFF Tags:YResolution", scaleY ) )
    {
        unitY = "nm"
        scaleY = 1e7/scaleY
    }
        /*
    if ( imported.GetStringNote("TIFF Tags:<X unit", scaletemp ) )
    {
        unitX = "nm"
        scalestart = scaletemp.find("\">") + 2
        scaleend = scaletemp.find("</X>")
        scaleX = 1e7/val(scaletemp.mid(scalestart,scaleend-scalestart))
    }
    if ( imported.GetStringNote("TIFF Tags:<Y unit", scaletemp ) )
    {
        unitY = "nm"
        scalestart = scaletemp.find("\">") + 2
        scaleend =scaletemp.find("</Y>")
        scaleY = 1e7/val(scaletemp.mid(scalestart,scaleend-scalestart))
    }
        */
        /*
    if ( imported.GetStringNote("TIFF Tags:Width", wStr ) )
    {
        number pos = find( wStr, " " )
        if ( -1 < pos )
        {
            scaleX = val( left(wStr,pos) )
            scaleX /= imported.ImageGetDimensionSize(0)
            unitX  = right( wStr, len(wStr)-pos-1 )
        }
    }
    if ( imported.GetStringNote("TIFF Tags:Height", hStr ) )
    {
        number pos = find( hStr, " " )
        if ( -1 < pos )
        {
            scaleY = val( left(hStr,pos) )
            scaleY /= imported.ImageGetDimensionSize(1)
            unitY  = right( hStr, len(hStr)-pos-1 )
        }
    }
        */
    if (0 < scaleX )
    {
        imported.ImageSetDimensionScale(0,scaleX)
        imported.ImageSetDimensionUnitString(0,unitX)
    }
    if (0 < scaleY )
    {
        imported.ImageSetDimensionScale(1,scaleY)
        imported.ImageSetDimensionUnitString(1,unitY)
    }

result("\n" + scaleX + "\n")
result(unitX)
// imported.ImageSetDimensionUnitString(0,unitX)
}
ImportTIFFWithTags()

标签： imageoffsettiffcalibrationdm-script

解决方案

好的，根据此处找到的信息，XResolution和YResolution标记的 ID 分别为 282 和 283。

使用上面的模板脚本并在您的示例数据上运行时查看信息性文本输出，可以得到：

 entry # 0: ID[256] typ=4   count=1  offset @ 4096
 entry # 1: ID[257] typ=4   count=1  offset @ 4096
 entry # 2: ID[258] typ=3   count=1  offset @ 16
 entry # 3: ID[259] typ=3   count=1  offset @ 1
 entry # 4: ID[262] typ=3   count=1  offset @ 1
 entry # 5: ID[273] typ=4   count=4096   offset @ 50970
 entry # 6: ID[278] typ=4   count=1  offset @ 1
 entry # 7: ID[279] typ=4   count=4096   offset @ 67354
 entry # 8: ID[282] typ=5   count=1  offset @ 83738
 entry # 9: ID[283] typ=5   count=1  offset @ 83746
 entry # 10: ID[296]    typ=3   count=1  offset @ 3
 entry # 11: ID[339]    typ=3   count=1  offset @ 1
 entry # 12: ID[37706]  typ=4   count=1  offset @ 83754
 entry # 13: ID[37707]  typ=1   count=1616   offset @ 49168
 entry # 14: ID[37708]  typ=7   count=6312   offset @ 83754

所以你可以看到，你的 TIFF 图像有 15 个目录条目，并且确实存在 ID 282 和 283 的标签并且是类型 5。哪个（再次使用这里的源）应该是类型的，就像你评论的那样在修改后的脚本中。该类型定义为两个长 (int32) 值。

这样，整个TIFF结构浏览就成功了，你只需要适应读出标签的部分。您已经过滤了类型 5，但最好另外过滤 ID 值。然后你需要读出这些值。它们不再是text，因此原始脚本使用了不正确的命令。本质上，而不是

if ( 2 == typ ) // ASCII
{
    number currentPos = fStream.StreamGetPos()
    fStream.StreamSetPos( 0, dataOffset )
    string textField = fStream.StreamReadAsText( 0, count )
    txt+=textField
    fStream.StreamSetPos( 0, currentPos )
}

你想做的

if ( 5 == typ ) // Rational (2 int32 values)
{
    number currentPos = fStream.StreamGetPos() // Remember Stream Pos
    fStream.StreamSetPos( 0, dataOffset ) // Set Stream to offset value as specified
    number n1,n2
    if ( 282 == tag )  // XResolution
    {
        n1 = fStream.ReadValueOfType( "long", byteOrder ) // Read long
        n2 = fStream.ReadValueOfType( "long", byteOrder ) // continue to read next long
        txt += "XResoltion:" + n1 + " / " + n2
    }
    else if ( 283 == tag )  // YResolution
    {
        n1 = fStream.ReadValueOfType( "long", byteOrder )
        n2 = fStream.ReadValueOfType( "long", byteOrder )
        txt += "YResoltion:" + n1 + " / " + n2
    }
    fStream.StreamSetPos( 0, currentPos )
}

请注意，这ReadValueOfType实际上只是脚本中定义的自制便利命令。底层 DM 脚本技术是创建特定类型的 TagGroup 对象并将其用作TagGroupReadTagDataFromStream命令中的代理。原始脚本没有long类型的值，因此您需要扩展此功能，即：

else if ( type == "long" )
{
    tg.TagGroupSetTagAsLong( type, 0 )
    tg.TagGroupReadTagDataFromStream( type, fstream, byteOrder ) 
    tg.TagGroupGetTagAsLong( type, val )
}

我猜你可能还想稍微重构一下整个脚本，因为你不需要读出这些值然后将它们转换成文本等。所以一个经过简化的调整脚本可能看起来像这样：

// Auxilliary method for stream-reading of values
number ReadValueOfType(object fStream, string type, number byteOrder)
{
    number val = 0
    TagGroup tg = NewTagGroup()
    if ( type == "bool" )
    {
        tg.TagGroupSetTagAsBoolean( type, 0 )
        tg.TagGroupReadTagDataFromStream( type, fstream, byteOrder ) 
        tg.TagGroupGetTagAsBoolean( type, val )
    }
    else if ( type == "uint16" )
    {
        tg.TagGroupSetTagAsUInt16( type, 0 )
        tg.TagGroupReadTagDataFromStream( type, fstream, byteOrder ) 
        tg.TagGroupGetTagAsUInt16( type, val )
    }
    else if ( type == "uint32" )
    {
        tg.TagGroupSetTagAsUInt32( type, 0 )
        tg.TagGroupReadTagDataFromStream( type, fstream, byteOrder ) 
        tg.TagGroupGetTagAsUInt32( type, val )
    }
    else if ( type == "long" )
    {
        tg.TagGroupSetTagAsLong( type, 0 )
        tg.TagGroupReadTagDataFromStream( type, fstream, byteOrder ) 
        tg.TagGroupGetTagAsLong( type, val )
    }
    else Throw("Invalid read-type:"+type)
    return val
}

number ExtractRationalTagOfIDFromTiff( string path, number ID, number &n1, number &n2, number ShowTIFFInfo )
{
    string txt
    if ( !DoesFileExist(path) ) 
        Throw("File not found.\n"+path)

    // Open Stream 
    number fileID = OpenFileForReading( path )
    object fStream = NewStreamFromFileReference(fileID,1)

    // Read data byte order. (1 = big Endian, 2= little Endian for Gatan)
    number val
    number byteOrder = 0
    val = fStream.ReadValueOfType( "uint16", byteOrder )
    byteOrder = ( 0x4949 == val  ) ? 2 : ( 0x4D4D == val ? 1 : 0 )
    if ( ShowTIFFInfo )
        Result("\n TIFF endian:"+byteOrder)

    // Verify TIFF image
    val = fStream.ReadValueOfType( "uint16", byteOrder )
    if ( val != 42 ) Throw( "Not a valid TIFF image" )

    // Browse all directories
    number offset = fStream.ReadValueOfType( "uint32", byteOrder )

    number success = 0
    while( 0 != offset )
    {
        fStream.StreamSetPos( 0, offset ) // Start of IFD
        number nEntries = fStream.ReadValueOfType( "uint16", byteOrder )
        for ( number e=0;e<nEntries;e++)
        {
            number tag        = fStream.ReadValueOfType( "uint16", byteOrder )
            number typ        = fStream.ReadValueOfType( "uint16", byteOrder )
            number count      = fStream.ReadValueOfType( "uint32", byteOrder )
            number dataOffset = fStream.ReadValueOfType( "uint32", byteOrder )
            if ( ShowTIFFInfo )
                Result("\n entry # "+e+": ID["+tag+"]\ttyp="+typ+"\tcount="+count+"\t offset @ "+dataOffset)

            if ( ( ID == tag )  && ( 5 == typ ) ) // Rational (2 long values)
            {               
                number currentPos = fStream.StreamGetPos()
                fStream.StreamSetPos( 0, dataOffset )
                n1 = fStream.ReadValueOfType( "long", byteOrder )
                n2 = fStream.ReadValueOfType( "long", byteOrder )
                success = 1
                fStream.StreamSetPos( 0, currentPos )

                if ( ShowTIFFInfo )
                    Result( " ==>" + n1 + " / " + n2 )
            }   
        }
        offset = fStream.ReadValueOfType( "uint32", byteOrder ) // this is 0000 for the last directory according to spec
    }

    return success
}

// Import and calibrate TVIPS Tiff images
void ImportCalibratedTVIPS_TIFF()
{
    string path = GetApplicationDirectory("open_save",0)
    if (!OpenDialog(NULL,"Select TVIPS TIFF file",path, path)) exit(0)

    // Import data 
    image imported := OpenImage(path)
    imported.ShowImage()

    // Calibrate image, stored as XResolution and YResolution tags
    number n1,n2
    number scaleX = 0
    number scaleY = 0
    if ( ExtractRationalTagOfIDFromTiff( path, 282,  n1, n2, 1 ) )
    {
        scaleX = n1/n2
        Result("\n X Resolution:" + Format( scaleX, "%g" ))
    }
    else
    {
        Result("\n X Resolution: NOT FOUND")
    }
    if ( ExtractRationalTagOfIDFromTiff( path, 283,  n1, n2, 0 ) )
    {
        scaleY = n1/n2
        Result("\n Y Resolution:" + Format( scaleY , "%g" ))
    }
    else
    {
        Result("\n Y Resolution: NOT FOUND")
    }
    if ( 0 != scaleX )
        imported.ImageSetDimensionScale( 1, scaleX )
    if ( 0 != scaleY )
        imported.ImageSetDimensionScale( 1, scaleY )
}

clearResults()
ImportCalibratedTVIPS_TIFF()

在您的图像数据上运行脚本，我得到：

 X Resolution:3.90786e+08
 Y Resolution:3.90786e+08

我不知道校准应该使用的单位，但值似乎有点高......（特别是对于 TEM 图像）？但是，对于 X 和 Y，它与您指定的应该相同。

顺便说一句，提供的 TIFF 图像似乎包含以下元信息：

ID[256] = Image Size X
ID[257] = Image Size Y
ID[258] = BitsPerSample
ID[259] = Compression
ID[262] = PhotometricInterpretation
ID[273] = StripOffsets
ID[278] = RowsPerStrip
ID[279] = StripByteCounts
ID[282] = XResolution
ID[283] = YResolution
ID[296] = ResolutionUnit
ID[339] = SampleFormat
ID[37706] = ????
ID[37707] = ????
ID[37708] = ????

从图像中读出分辨率单位给出：
Resolution Unit:24576

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