top of page

Redefining industry standards through innovation.

Welcome!

Welcome to PixMaster, where we specialise in cutting-edge image processing technology development, focusing particularly on advanced algorithms for image correction. With a robust portfolio of innovative solutions, we have successfully solved a few of the biggest challenges in the field of digital image enhancement and restoration.

​

We are committed to pushing the boundaries of visual quality and accuracy through rigorous research and development. By leveraging state-of-the-art technologies and methodologies, we empower businesses and professionals to achieve superior results with their visual content.

Color Balance

Problem

1. The Persistent Challenge of Color Correction in Image Editing
No single solution currently exists that can effectively address the majority of color-related issues in images. While numerous color-balancing tools are available—such as Color Balance, Levels, Curves, Selective Color, Photo Filter, and Camera Raw’s Temperature/Tint adjustments—each has limitations in solving different types of color problems.

The typical workflow often becomes a process of trial and error: users first attempt Color Balance adjustments. If unsuccessful, they may try channel adjustments in Levels or Curves. When these methods fail, Selective Color corrections are often attempted. As a last resort, many apply Photo Filters or adjust Temperature and Tint in Camera Raw Filter.

This sequential experimentation creates significant uncertainty, as there is no reliable way to predict which method will successfully correct color issues in any given image. 
 

2. The Challenge of Selecting Appropriate Color Correction Methods
A significant challenge in color correction lies in accurately identifying the most suitable adjustment method for each specific color problem. For instance, when presented with six different images exhibiting distinct color issues, would you be able to confidently determine which correction technique - whether Color Balance, Levels, Curves, or Selective Color - would yield optimal results for each case?
 

Solution

Our advanced color balance technology resolves the majority of color correction challenges, eliminating the need for users to toggle between multiple adjustment tools and settings.

Please watch the video, where we demonstrate how to correct various images with different color issues using just one solution: our advanced Color Balance option.

Anchor_ColorBalance

Ultimate Color Control

Problem

We have not come across any image processing option that can separate colors strictly according to theoretical principles.

Now, let's understand the fundamental theory behind color separation, which should be followed:
 

  • Tertiary colors are created by mixing primary and secondary colors, as shown in the  image (A). For example, orange is formed by mixing red and yellow. If red is completely removed from the image, as shown in the  image (B), it should also be removed from orange, leaving a shade of yellow in its place.

 

  • If red, green, and blue are entirely removed from an image, as shown in the  image (C), the areas originally containing these colors should appear gray. The luminance values should follow the correct order: blue should have the lowest luminance, followed by red, and then green.

 

  • According to the standard grayscale conversion formula (Y=0.299R+0.587G+0.114B),  the expected luminance values are:​

  • Blue: 29

  • Red: 76

  • Green: 150

Solution

Our technology precisely separates colors according to established color theory principles. This advancement has valuable applications across multiple fields, including:

  • Biomedical research

  • Robotics

  • Developing Image processing algorithms

Please watch the video, where we explain the problem and solution in detail. Additionally, we demonstrate its practical use in biomedical research and the development of image processing algorithms.

Anchor_UltimateColorControl

Light Recovery

Problem

When recovering proper tones from slightly overexposed areas, we typically observe a grayish cast in the highlight-recovered regions.

Original                                                                                 PixMaster                                                                                  Others

Solution

Our light recovery process aims to restore the natural tones present in the image’s overexposed areas without introducing a grayish casts to the recovered regions.

Please watch our demonstration video, which compares our Light Recovery technology with both Photoshop's Shadow/Highlight option and the Highlight adjustment in Camera Raw Filter.

Anchor_LightRecovery

Color Contrast

Problem

In contrast adjustments, when bright areas become brighter, they lose color gradation, leading to overexposure or clipping, especially if the subject is white or light-colored.

Original                                                                                 PixMaster                                                                                  Others

Solution

Our color contrast technique prevents bright areas from becoming brighter, preserving color gradation even in the brightest regions—unlike conventional contrast adjustments in Photoshop or similar applications.

You might assume that using blending modes like Darken or applying a luminosity mask to contrast adjustments could achieve this. However, these methods merely limit contrast in bright areas, effectively removing contrast rather than preserving it.

In color contrast, our approach applies contrast from dark to light areas without increasing brightness in already bright regions. This ensures complete control over the image, allowing you to adjust whites or exposure independently afterward.

Please watch the video below, where we compare color contrast with conventional contrast adjustments.

Anchor_ColorContrast

Dark Recovery

Dark Recovery enhances details in darker areas of the image, aiming to achieve results that closely resemble what you saw with your own eyes.

Anchor_DarkRecovery

Local Contrast

Local contrast enhancement improves image quality by introducing depth and a three-dimensional effect, similar to that achieved with premium camera lenses. This technique accentuates fine details and textures, enhancing visual clarity and creating a more dynamic, lifelike representation.

Anchor_LocalContrast

Vibrance

This intelligent option allows you to enhance saturation in less colorful parts of the image without affecting already vibrant areas, thus preserving natural color balance. This prevents colors from appearing unnatural and ensures that skin tones remain natural and not overly saturated. Conversely, applying negative vibrance can reduce saturation, starting with the most vibrant colors and gradually affecting the rest of the image.

Capture.PNG
Anchor_Vibrance

Luminance Adjustment

The "Luminance Adjustment" option in PixMaster is a powerful tool for controlling the brightness or darkness of specific colors in your image.

  • Increasing Luminance: When you increase the luminance of a color (for example, blue), it makes that color brighter in the image. This means areas that are predominantly blue will appear lighter.

  • Decreasing Luminance: Conversely, decreasing the luminance of a color darkens that specific color in the image. This adjustment is useful for making colors appear deeper or more muted.

Anchor_LuminanceAdjust
bottom of page