We will continue to talk about various techniques for processing true-color images in the next post.The ability to acquire images in vivo in intact organisms provides a wealth of physiological and pathological information that is not available when analyzing cells or tissues ex vivo. That’s all I want to cover pseudocolor image processing.
This is an important technique for space-based images, or document and painting analysis. Multispectral image processing allows us to infer the wavelengths that cannot be captured by the conventional RGB cameras or even human eyes. We often come across multispectral images in remote sensing systems, for example, Landsat Thematic Mapper (TM) Band 7 which targets the detection of hydrothermal This technique is called multispectral image processing. The flexibility can be even more enhanced by using more than one monochrome images, for example, the three components of an RGB and the thermal image. Functional block diagram for pseudocolor image processing. We can generalize the above technique by performing three independent transformations on the intensity of the image, resulting in three images which are the red, green, blue component images used to produce a color image. Result of density slicing into eight colors. In this case, the grayscale is parted into intervals and each one is assigned a different color. Multiple slices result in more flexible representations of the grayscale images. We are not constrained to use only one plane. Geometric interpretation of the intensity slicing technique. After that we can assign different colors to different levels. Placing a plane parallel to the horizontal plane for the pixel position coordinates would “slice” the image into two parts. Imagine a grayscale image as a 3D function with the intensity being the third dimension. It’s also called density slicing or color coding.
This is a simple case of pseudocolor image processing. Another example is elevation map.Įxamples for pseudocolor images Intensity Slicing Typical usage of these images is for thermography where the only available is infrared radiation instead of lights. Pseudocolor images are originally grayscale which are assigned colors based on the intensity values. False color image VS True color Landsat image They are mainly used for satellite and space images. It’s difficult to achieve absolute true color in images, but being approximately close to human perception is acceptable.įalse color images, on the other hand, sacrifices natural color rendition in order to facilitate the detection of some objects. True-color images are images with natural color rendition: a red apple appears red, a blue ocean appears blue, etc. True color VS false colorīefore talking about false color, what does true color mean anyway? In this post, we will talk about the first one. There two main categories of color image processing: pseudocolor (false colo r) image processing and full-color image processing. You can read about how colors are perceived and common color models in my first post. This is the second post on the report of Chapter 6 from the book Digital Image Processing (Rafael C.
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