Need help: Brightness conversion

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In summary, the speaker is having difficulties comparing different brightness data of the sky, particularly when converting between units such as m(vis)/deg^2 and m(vis)/sr. They have identified some potential issues with their conversions and are seeking assistance in finding where they may have gone wrong. Suggestions for improving the comparison process include double checking conversion factors, considering the angular size of measurements, and checking for any missing factors in the calculations.
  • #1
MET
I have difficulties to compare different brightness data of the sky.

In older literature I found different measurements of the brightness density of the sky. Some of the results are shown in in m(vis)/deg^2 and others in asb. In order to compare the data in units of m(vis)/sterad, I proceeded as follows:

The asb values:
1 Lux / sr = asb * Pi
since 1 Lux corresponds to -14.18 m(vis)
1 asb = - 1 / Pi * 14.18 m(vis) / sr
for the conversion I calculate
m(vis)/sr value corresponds to -14.18 - 2.5*LOG10( Pi * asb value )

For m(vis)/deg^2 values:
m(vis)/sr value corresponds to m(vis)/deg^2 value - 2.5*LOG10( (180/Pi)^2 ) = m(vis)/deg^2 value - 8.79

The results show me that doing so is not correct! However, the difference of around. 2.67 m(vis)/sr indicates some where a missing factor of 4*Pi. In the conversion of the m(vis)/deg^2 values, a possible 4*Pi-factor in the LOG10-expression was omitted intentionally since the 'per degrees' are converted in 'per radians' and not for the full sphere.

Could some one please indicate me where I am doing wrong. Thank you.
 
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Hello there,

Thank you for sharing your difficulties with comparing different brightness data of the sky. It seems like you have a good understanding of the units and conversions involved, but there may be a few factors that you have missed. Here are some suggestions to help you in your comparison:

1. Make sure you are using the correct conversion factors: It is important to double check the conversion factors you are using for each unit. For example, 1 Lux corresponds to -14.18 m(vis)/deg^2, not m(vis)/sr. Also, 1 asb corresponds to -14.18 m(vis)/sr, not m(vis)/deg^2. Make sure you are using the correct factors for each unit to get accurate results.

2. Consider the angular size of your measurements: When comparing brightness data, it is important to consider the angular size of the measurements. For example, a measurement in m(vis)/deg^2 will have a different angular size than a measurement in m(vis)/sr. This could also explain the difference of 2.67 m(vis)/sr that you observed in your results. Make sure to take into account the angular size of each measurement when converting between units.

3. Check for any missing factors: As you mentioned, there could be a missing factor of 4*Pi in your conversion. This could be due to the fact that you are converting from m(vis)/deg^2 to m(vis)/sr, which involves converting from degrees to radians. Make sure to double check your calculations and include any necessary factors to get accurate results.

I hope these suggestions are helpful in resolving your difficulties with comparing brightness data of the sky. It is important to pay close attention to the units and conversions involved to ensure accurate comparisons. If you continue to have trouble, I would suggest consulting with a colleague or supervisor for further guidance. Good luck!
 

1. What is brightness conversion?

Brightness conversion is the process of converting the brightness or luminance of an image from one unit of measurement to another. This is often done to adjust the overall brightness of an image or to convert from one color space to another.

2. How is brightness measured in images?

Brightness in images is typically measured using a unit of luminance called the candela per square meter (cd/m²). This unit measures the amount of light energy emitted or reflected from a surface.

3. What are the different methods of brightness conversion?

There are several methods of brightness conversion, including gamma correction, histogram equalization, and linear scaling. Gamma correction is commonly used to adjust the overall brightness of an image, while histogram equalization is used to enhance the contrast of an image. Linear scaling is often used to convert from one color space to another.

4. Why is brightness conversion important in image processing?

Brightness conversion is important in image processing because it allows for the adjustment of the overall brightness and contrast of an image. This can help improve the visual quality of an image or make it more suitable for a specific display or printing medium.

5. Are there any tools or software available for performing brightness conversion?

Yes, there are many tools and software available for performing brightness conversion, such as Adobe Photoshop, GIMP, and ImageMagick. These programs offer various methods for adjusting the brightness of images and converting between different color spaces.

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