174 lines
7.7 KiB
TeX
174 lines
7.7 KiB
TeX
\section{The VIPS file format}
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VIPS has its own very simple file format. It is used inside VIPS to hold
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images during computation. You can save images in VIPS format if you want,
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but the VIPS format is not widely used and you may have problems reading
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your images into other packages.
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If you intend to keep an image, it's much better to save it as TIFF,
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JPEG, PNG, PBM/PGM/PPM or HDR. VIPS can transparently read and write all
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these formats.
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\subsection{VIPS file header}
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\label{sec:header}
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All VIPS image files start with a 64-byte header giving basic information
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about the image dimensions, see \tref{fg:header}. This is followed by the
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image data. This is usually just the pixel values in native format (ie. the
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byte order used by the machine that wrote the file) laid out left-to-right and
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top-to-bottom. After the image data comes a block of optional XML which holds
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extra image metadata, such as ICC profiles and image history.
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You can use the command-line program \verb+header+ to extract the XML from an
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image and \verb+edvips+ to replace it, see the man pages.
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The \ct{Type} field, the \ct{Xres}/\ct{Yres} fields, and the
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\ct{Xoffset}/\ct{Yoffset} fields are advisory. VIPS maintains their value
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(if you convert an image to \cielab{} colour space with \ct{im\_XYZ2Lab()},
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for example, VIPS will set \ct{Type} to be \ct{IM\_TYPE\_LAB}), but never
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uses these values itself in determining the action of an image processing
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function. These fields are to help the user and to help application
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programs built on VIPS which are trying to present image data to the user
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in a meaningful way.
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The \ct{BandFmt}, \ct{Coding} and \ct{Type} fields can take the values
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shown in tables~\ref{fg:bandfmt}, \ref{fg:coding} and \ref{fg:type}. The C++
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and Python names for these values are slightly different, for historical
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reasons.
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\begin{tab2}
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\begin{center}
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\begin{tabular}{|l|l|l|}
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\hline
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Bytes & Represent & VIPS name \\
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\hline
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0--3 & VIPS magic number (in hex, 08 f2 f6 b6) & \\
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4--7 & Number of pels per horizontal line (integer) & \ct{Xsize} \\
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8--11 & Number of horizontal lines (integer) & \ct{Ysize} \\
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12--15 & Number of bands (integer) & \ct{Bands} \\
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16--19 & Unused (legacy) & \ct{Bbits} \\
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20--23 & Band format (eg. \ct{IM\_BANDFMT\_USHORT}) & \ct{BandFmt} \\
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24--27 & Coding type (eg. \ct{IM\_CODING\_NONE}) & \ct{Coding} \\
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28--31 & Type (eg. \ct{IM\_TYPE\_LAB}) & \ct{Type} \\
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32--35 & Horizontal resolution (float, pixels mm$^{-1}$) & \ct{Xres} \\
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36--39 & Vertical resolution (float, pixels mm$^{-1}$) & \ct{Yres} \\
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40--43 & Unused (legacy) & \ct{Length} \\
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44--45 & Unused (legacy) & \ct{Compression} \\
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46--47 & Unused (legacy) & \ct{Level} \\
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48--51 & Horizontal offset of origin & \ct{Xoffset} \\
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52--55 & Vertical offset of origin & \ct{Yoffset} \\
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56--63 & For future expansion (all zeros for now) & \\
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\hline
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\end{tabular}
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\end{center}
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\caption{VIPS header\label{fg:header}}
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\end{tab2}
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\begin{tab2}
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\begin{center}
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\begin{tabular}{|l|l|l|l|}
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\hline
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\ct{BandFmt} & C++ and Python name & Value & Meaning \\
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\hline
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\ct{IM\_BANDFMT\_NOTSET} & \ct{FMTNOTSET} & -1 & \\
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\ct{IM\_BANDFMT\_UCHAR} & \ct{FMTUCHAR} & 0 & Unsigned 8-bit int \\
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\ct{IM\_BANDFMT\_CHAR} & \ct{FMTCHAR} & 1 & Signed 8-bit int \\
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\ct{IM\_BANDFMT\_USHORT} & \ct{FMTUSHORT} & 2 & Unsigned 16-bit int \\
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\ct{IM\_BANDFMT\_SHORT} & \ct{FMTSHORT} & 3 & Signed 16-bit int \\
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\ct{IM\_BANDFMT\_UINT} & \ct{FMTUINT} & 4 & Unsigned 32-bit int \\
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\ct{IM\_BANDFMT\_INT} & \ct{FMTINT} & 5 & Signed 32-bit int \\
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\ct{IM\_BANDFMT\_FLOAT} & \ct{FMTFLOAT} & 6 & 32-bit IEEE float \\
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\ct{IM\_BANDFMT\_COMPLEX} & \ct{FMTCOMPLEX} & 7 & Complex (2 floats) \\
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\ct{IM\_BANDFMT\_DOUBLE} & \ct{FMTDOUBLE} & 8 & 64-bit IEEE double \\
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\ct{IM\_BANDFMT\_DPCOMPLEX} & \ct{FMTDPCOMPLEX} & 9 & Complex (2 doubles) \\
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\hline
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\end{tabular}
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\end{center}
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\caption{Possible values for \ct{BandFmt}\label{fg:bandfmt}}
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\end{tab2}
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\begin{tab2}
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\begin{center}
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\begin{tabular}{|l|l|l|l|}
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\hline
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\ct{Coding} & C++ and Python name & Value & Meaning \\
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\hline
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\ct{IM\_CODING\_NONE} & \ct{NOCODING} & 0 & VIPS computation format \\
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\ct{IM\_CODING\_LABQ} & \ct{LABQ} & 2 & LABQ storage format \\
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\ct{IM\_CODING\_RAD} & \ct{RAD} & 6 & Radiance storage format \\
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\hline
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\end{tabular}
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\end{center}
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\caption{Possible values for \texttt{Coding}\label{fg:coding}}
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\end{tab2}
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\begin{tab2}
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\begin{center}
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\begin{tabular}{|l|l|l|l|}
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\hline
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\ct{Type} & C++ and Python name & Value & Meaning \\
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\hline
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\ct{IM\_TYPE\_MULTIBAND} & \ct{MULTIBAND} & 0 & Some multiband image \\
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\ct{IM\_TYPE\_B\_W} & \ct{B\_W} & 1 & Some single band image \\
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\ct{IM\_TYPE\_HISTOGRAM} & \ct{HISTOGRAM} & 10 & Histogram or LUT \\
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\ct{IM\_TYPE\_FOURIER} & \ct{FOURIER} & 24 & Image in Fourier space \\
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\ct{IM\_TYPE\_XYZ} & \ct{XYZ} & 12 & \ciexyz{} colour space \\
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\ct{IM\_TYPE\_LAB} & \ct{LAB} & 13 & \cielab{} colour space \\
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\ct{IM\_TYPE\_CMYK} & \ct{CMYK} & 15 & \ct{im\_icc\_export()} \\
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\ct{IM\_TYPE\_LABQ} & \ct{LABQ} & 16 & 32-bit \cielab{} \\
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\ct{IM\_TYPE\_RGB} & \ct{RGB} & 17 & Some RGB \\
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\ct{IM\_TYPE\_UCS} & \ct{UCS} & 18 & \cieucs{} colour space \\
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\ct{IM\_TYPE\_LCH} & \ct{LCH} & 19 & \cielch{} colour space \\
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\ct{IM\_TYPE\_LABS} & \ct{LABS} & 21 & 48-bit \cielab{} \\
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\ct{IM\_TYPE\_sRGB} & \ct{sRGB} & 22 & sRGB colour space \\
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\ct{IM\_TYPE\_YXY} & \ct{YXY} & 23 & \cieyxy{} colour space \\
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\ct{IM\_TYPE\_RGB16} & \ct{RGB16} & 25 & 16-bit RGB \\
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\ct{IM\_TYPE\_GREY16} & \ct{GREY16} & 26 & 16-bit monochrome \\
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\hline
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\end{tabular}
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\end{center}
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\caption{Possible values for \texttt{Type}\label{fg:type}}
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\end{tab2}
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\subsection{Computation formats}
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This type of image has \ct{Coding} set to \ct{IM\_CODING\_NONE}. The
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header is then followed by a large array of pixels, laid out left-to-right,
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top-to-bottom. Each pixel contains the specified number of bands. Each band
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has the specified band format, which may be an 8-, 16- or 32-bit integer
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(either signed or unsigned), a single or double precision IEEE floating
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point number, or a pair of single or double precision floats forming a
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complex number.
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All values are stored in the host-machine's native number representation (that
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is, either most-significant first, as in SPARC and 680x0 machines, or
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least-significant first, for Intel and DEC machines). If necessary, the VIPS
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library will automatically byte-swap for you during read.
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\subsection{Storage formats}
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All storage formats have other values for the \ct{Coding} field. This
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release supports \ct{IM\_CODING\_LABQ} and \ct{IM\_CODING\_RAD}.
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\ct{IM\_CODING\_LABQ} stores $L^{*}$, $a^{*}$ and $b^{*}$ for each pixel,
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with 10 bits for $L^{*}$ and 11 bits for each of $a^{*}$ and $b^{*}$. These
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32 bits are packed into 4 bytes, with the most significant 8 bits of each
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value in the first 3 bytes, and the left-over bits packed into the final
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byte as 2:3:3.
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This format is a little awkward to process. Some VIPS functions can work
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directly on \ct{IM\_CODING\_LABQ} images (\ct{im\_extract\_area()}, for
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example), but most will require you to unpack the image to one of the
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computation formats (for example with \ct{im\_LabQ2Lab()}) first.
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\ct{IM\_CODING\_RAD} stores $RGB$ or $XYZ$ float images as 8 bytes of mantissa
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and then 8 bytes of exponent, shared between the three channels. This coding
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style is used by the Radiance family of programs (and the HDR format) commonly
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used for HDR imaging. This style of image is generated when you load an HDR
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image.
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This format is a little awkward to process. Some VIPS functions can work
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directly on \ct{IM\_CODING\_RAD} images (\ct{im\_extract\_area()}, for
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example), but most will require you to unpack the image to one of the
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computation formats with \ct{im\_rad2float()} first.
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