cPicture

Postage

This function plugin turns selected pictures into postage stamps with a perforated border.
The dialog lets you configure the paper style, border spacing, text, text corner, font and text color.

Index print created with cPicture
(Perforation 4, Distance 8, Offwhite paper with default font, Standard Index print with no border)

Download the plugin from Function plug-ins menu and select Manage in cPicture.
See the plugin overview

Time Capsule

This function plugin creates a story poster from multiple selected pictures with title, route strip, location clusters, summary and thumbnails. The dialog lets you configure the sorting mode, location radius and thumbnail size.
The route is built from available GPS data and linked to the picture thumbnails, creating a visual summary of a trip, series or shoot.

Created with cPicture's map view:

X-Ray

This function plugin creates an analysis board for each selected picture with the original view, an edge map, an 8x8 block analysis and a combined heat map. Scale, sensitivity and the optional 8x8 grid can be configured in the dialog.
The output helps highlight structures, compression artifacts and visually suspicious image regions.

Motion Composer

This function plugin combines multiple pictures into a single composition with motion and trail effects. Output size, threshold and optional trail colorization are configured in the dialog.
It is especially useful for sequences with movement, such as people, vehicles or repeated actions.

Composed from these two pictures:
Created with the Sample plugin #5

Download the plugin from Function plug-ins menu and select Manage in cPicture.
See the plugin overview

Plugin QR-Code

Overlays a QR code onto your pictures. Enter any text or URL, choose the corner position, and adjust size and margin with sliders.

Download the plugin from Function plug-ins menu and select Manage in cPicture.
See the plugin overview

cPicture is updated to version 4.10

• added new JPEG10 Lossless Exposure & Contrast Adjustment
  
  
  Exposure compensation from -2EV to +2EV:

  
  Contrast from -1CV to +1CV:

  

  See this blog entry
  
  

• Updated format plugin version to 4.10
• Maintenance update and minor changes

cPicture is a portable application consisting of a single .exe file and optional plugin files.

Download the MSI file to copy the app to a folder or use the 'Check for updates' button in the 'Other' category.

Download German 64bit Installer MSI
Download English 64bit Installer MSI
More languages are available from the cPicture site.
Alternative download from github

See the Download Instructions for more details.

For questions, please mail to: cpicture

Lossless Tonal Adjustments in JPEG's DCT Domain: Exposure Compensation and Multi-Band Contrast

Most JPEG workflows treat exposure (brightness) and contrast as inherently "lossy": decode pixels, apply curves, then re-encode. That approach works, but it always introduces an additional step of quantization error.

In this github fork of the IJG JPEG-10 code, I added two options to jpegtran that operate directly on quantized DCT coefficients:

• -exposure-comp EV
• -contrast DC LOW MID HIGH

Both are applied during transcoding, so they combine naturally with existing jpegtran operations such as rotation, flipping, cropping, marker copying, and progressive conversion.

https://github.com/jurgen178/jpeg10
Download Windows x64 binary: jpegtran.zip

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Quick Usage

jpegtran [standard options] [-exposure-comp EV] [-contrast DC LOW MID HIGH] input.jpg output.jpg

Examples:

# Brighten by 1 stop
jpegtran -copy all -exposure-comp 1 input.jpg output.jpg

# Darken by 0.5 stops
jpegtran -copy all -exposure-comp -0.5 input.jpg output.jpg

# Contrast (uniform: DC=LOW=MID=HIGH)
jpegtran -copy all -contrast -1   -1   -1   -1   input.jpg out-contrast-u-1.jpg
jpegtran -copy all -contrast -0.5 -0.5 -0.5 -0.5 input.jpg out-contrast-u-0.5.jpg
jpegtran -copy all -contrast  0.5  0.5  0.5  0.5 input.jpg out-contrast-u+0.5.jpg
jpegtran -copy all -contrast  1    1    1    1   input.jpg out-contrast-u+1.jpg

# Contrast (band-specific examples)
jpegtran -copy all -contrast 0 0 0.6 0   input.jpg out-contrast-mid+0.6.jpg
jpegtran -copy all -contrast 0 0 0 0.4   input.jpg out-contrast-high+0.4.jpg
jpegtran -copy all -contrast 0 0.4 0 0   input.jpg out-contrast-low+0.4.jpg

# Combine: rotate 90°, brighten 0.5 EV, and add uniform contrast +0.5
jpegtran -copy all -rot 90 -exposure-comp 0.5 -contrast 0.5 0.5 0.5 0.5 input.jpg output.jpg

Both switches accept fractional values. Practical ranges:

Option	Practical range	Neutral
-exposure-comp EV	-3 … +3	0
-contrast DC LOW MID HIGH	-2 … +2	0

Integrated into cPicture with live preview:

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Background: DCT Coefficient Basics

A JPEG image is encoded as a grid of DCT blocks (with 8×8 Elements in size). Each block has one DC coefficient and 63 AC coefficients. But each MCU might have more than one block depending on the color subsampling.

• DC[0] represents the (level-shifted) average sample value of the block. The relationship to pixel mean is:

  $$\mu = \frac{DC_\text{unquant}}{N} + \text{center}$$

  where $N$ is the DCT block size of 8 and $\text{center} = 2^{\text{precision}-1}$ (e.g. 128 for 8‑bit).

• AC[1..N²−1] represent spatial frequency components (texture, edges, contrast).

Both DC and AC are stored quantized: the actual stored integer is $\text{round}(\text{value} / Q_k)$, where $Q_k$ is the quantization step for coefficient $k$.

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-exposure-comp EV — Exposure Compensation

Exposure compensation from -2EV to +2EV:

Concept

A photographic EV step corresponds to doubling (or halving) the amount of light. Applied in linear light:

$$\text{gain} = 2^{EV}$$

Because JPEG samples are gamma-coded (sRGB), pixel values cannot be multiplied directly. Instead:

1. Estimate a representative level from the DC blocks.
2. Compute the equivalent additive pixel-domain offset by applying the gain in linear light at that reference level.
3. Translate the offset into a quantized DC delta.
4. Add the delta to every DC coefficient.

Only DC is modified. AC coefficients are not modified, so local contrast and texture are preserved.

Reference Level — Log-Average

A geometric mean (log-average) of all block mean levels is used as the exposure reference:

$$\bar{L} = \exp\!\left(\frac{1}{B}\sum_{i=1}^{B} \ln(L_i + 1)\right) - 1$$

where $L_i$ is the intensity mean of block $i$ (clamped to $[0, \text{MAX}]$) and $B$ is the total number of blocks.

sRGB Linearisation

The gain is applied in linear light:

$$u_\text{ref} = \frac{\bar{L}}{\text{MAX}}$$

$$u_\text{ref,lin} = f_\text{lin}(u_\text{ref})$$

$$u_\text{new,lin} = \min(u_\text{ref,lin} \cdot \text{gain},\; 1.0)$$

$$u_\text{new} = f_\text{sRGB}(u_\text{new,lin})$$

The sRGB transfer functions used:

$$f_\text{lin}(u) = \begin{cases} u / 12.92 & u \le 0.04045 \\ \left(\dfrac{u + 0.055}{1.055}\right)^{2.4} & u > 0.04045 \end{cases}$$

$$f_\text{sRGB}(u) = \begin{cases} 12.92\,u & u \le 0.0031308 \\ 1.055\,u^{1/2.4} - 0.055 & u > 0.0031308 \end{cases}$$

Pixel-Domain Offset → Quantized DC Delta

$$\Delta_\text{samples} = (u_\text{new} - u_\text{ref}) \cdot \text{MAX}$$

Clamped to available headroom/shadow room to limit clipping, then converted to a quantized DC delta:

$$\Delta_{DC} = \text{round}\!\left(\frac{\Delta_\text{samples} \cdot N}{Q_0}\right)$$

where $N$ is the DCT block size and $Q_0$ is the DC quantization step.

Component Policy

Color space	Components adjusted
YCbCr, BG_YCC, YCCK	Luma only (component 0)
RGB/BG_RGB + subtract-green transform	Green/base only (component 1)
CMYK, all others	All components

For CMYK and YCCK the delta is computed in an inverted intensity domain ($I = \text{MAX} - \text{sample}$) so that +EV brightens and −EV darkens.

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-contrast DC LOW MID HIGH — Contrast Adjustment

Contrast from -1CV to +1CV:

Concept

This option provides four separate controls (all in stops):

• DC controls the DC coefficient (block mean)
• LOW, MID, HIGH control the AC coefficients in frequency order

All controls are interpreted as log2 gains (stops). For a value $x$, the gain is:

$$g(x) = 2^{x}$$

So +1 doubles, -1 halves.

DC

DC is scaled by:

$$g_\mathrm{DC} = 2^{DC}$$

and applied as:

$$DC' = \mathrm{clamp}(\mathrm{round}(g_\mathrm{DC} \cdot DC))$$

AC (low/mid/high weighting)

AC coefficients are processed in zigzag order (the JPEG natural order). Let $z$ be the AC position with $z = 1 \ldots A$, where $A$ is the number of AC coefficients.

Define a normalized position:

$$t = \begin{cases} \dfrac{z-1}{A-1} & A > 1 \\ 0 & A = 1 \end{cases}$$

Triangular weights:

• low weight fades out from low frequencies

$$w_\mathrm{low} = \max(0, 1 - 2t)$$

• mid weight peaks in the middle

$$w_\mathrm{mid} = 1 - |2t - 1|$$

• high weight fades in toward high frequencies

$$w_\mathrm{high} = \max(0, 2t - 1)$$

Per-coefficient exponent and gain:

$$v(z) = LOW\cdot w_\mathrm{low} + MID\cdot w_\mathrm{mid} + HIGH\cdot w_\mathrm{high}$$

$$g(z) = 2^{v(z)}$$

Applied to each AC coefficient:

$$AC'[z] = \mathrm{clamp}(\mathrm{round}(g(z)\cdot AC[z]))$$

If DC = LOW = MID = HIGH = X, then all coefficients are scaled by the same gain $2^X$ (uniform contrast adjustment).

Component Policy

Same as -exposure-comp:

• YCbCr/BG_YCC/YCCK: luma only
• RGB subtract-green: base/green only
• otherwise: all components

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Ordering and Composition

Both -exposure-comp and -contrast are applied as a post step after any geometric transform (-rot, -flip, -crop, …). The tonal operations work on the final output coefficient arrays, so the order of switches on the command line does not matter.

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Implementation notes

• Core implementation:
  • transupp.c: do_exposure_comp() and do_contrast()
  • transupp.h: adds new fields to jpeg_transform_info
• CLI parsing:
  • jpegtran.c
• Feature flags and parameters are stored in jpeg_transform_info in transupp.h

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Summary

• -exposure-comp EV shifts brightness by changing only DC coefficients, with EV evaluated in linear light (sRGB transfer) at a log-average reference.
• -contrast DC LOW MID HIGH scales DC and AC coefficients, with AC gains varying smoothly over frequency order using low/mid/high controls.
• Both run in the DCT domain and integrate naturally into the lossless-transformation workflow of jpegtran.

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Example pictures