Basler немедленно прекращает все поставки своим российским и белорусским клиентам.


Ваш браузер устарел. Он имеет уязвимости в безопасности и может не показывать все возможности на этом и других сайтах. Узнайте, как обновить Ваш браузер .

Начните настройку системы машинного зрения Webshop

What are color filters?

Color Filters for Single-Sensor Color Cameras

In general single-sensor color cameras use a monochrome sensor with a color filter pattern. Another way to achieve a color image with only one sensor would be to use a revolving filter wheel in front of a monochrome sensor, but this method has its limitations.

With the color filter pattern method of color imaging, no object point is projected on more than one sensor pixel, that is, only one measurement (for a single color or sum of a set of colors) can be made for each object point.

There are several different filter methods for generating a color image from a monochrome sensor. In the following some frequently used filter arrangements are detailed.

Bayer Color Filter (Primary Color Mosaic Filter)

The following table 1 shows the filter pattern for a sensor of size xs x ys (xs and ys being multiples of 2):

Complementary Color Mosaic Filter

The following table 2 shows the filter pattern for a sensor of size xs x ys (xs and ys being multiples of 2):

This is basically the same arrangement as the Bayer filter pattern, but instead of using primary colors (R, G, B) it works with complementary colors (magenta, cyan, yellow). The reason for this is that a primary color filter blocks of 2/3 of the spectrum (i.e. green and blue for a red filter) while a complementary filter blocks only 1/3 of the spectrum (i.e. blue for a yellow filter). Thus, the sensor is 2 times more sensitive. The tradeoff is a somewhat more complicated computation of the R, G, B values, requiring the input of each complementary color.

Primary Color Vertical Stripe Filter

Table 3 shows the filter pattern for a sensor of size xs x ys (xs being a multiple of 4):

This arrangement is very simple and basically well suited to machine vision applications. The drawback is that the horizontal resolution is only 1/3 of the vertical resolution.