Method and apparatus providing rule-based auto exposure technique preserving scene dynamic range

1. A method for using an image processor, comprising:

with an image processing chain in the image processor, receiving image signals representing an image;

with the image processing chain, collecting automatic exposure data for a scene;

with the image processing chain, setting a luminance target level to an initial value;

with the image processing chain, determining a maximum value for the luminance target level, wherein determining the maximum value includes calculating the maximum value based on an average scene luminance multiplied by a predetermined constant and calculating the maximum value if the luminance target level clips highlights of the scene;

with the image processing chain, adjusting the luminance target level from its initial value to the maximum value;

with the image processing chain, adjusting tonal correction parameters;

with the image processing chain, adjusting S-curve parameters; and

with the image processing chain, adjusting image parameters for the scene and providing the image parameters to an image processing circuit for processing the scene.

2. The method defined in claim 1 wherein the average scene luminance is determined based on average luminance values associated with a plurality of image windows.

3. The method defined in claim 1 wherein the average scene luminance is determined based on average luminance values associated with image windows that cover a backlit object if backlighting is determined to be present in the scene.

4. The method defined in claim 1 , wherein collecting the automatic exposure data comprises:

collecting a scene exposure level, noise level, scene contrast level, and a highlights level of the scene based on a plurality of image windows.

5. The method defined in claim 4 , wherein adjusting the tonal correction parameters comprises:

adjusting the tonal correction parameters to increase low and midtones of the scene if the luminance target level and the noise level of scene are below respective thresholds.

6. A method of capturing an image, comprising:

examining light levels within a scene;

setting an exposure level for the scene;

setting a luminance target level to an initial value for scene exposure based on the exposure level;

adjusting the luminance target level from its initial value to a new value, wherein adjusting the luminance target level includes:

determining the new value for the luminance target level based on an average scene luminance level and a level of scene highlights; and

determining whether the new value exceeds the average scene luminance level; and

in response to determining that the new value is less than the average scene luminance level, decreasing the average scene luminance level to the new value;

using the adjusted value of the luminance target level to determine a new exposure level for the scene; and

capturing an image with the new exposure level.

7. The method of claim 6 , wherein adjusting the luminance target level from its initial value to the adjusted value further includes:

limiting the new value to be within a specific range of values based on the initial value of the luminance target level.

8. The method of claim 6 , further comprising:

determining if a scene has no highlights beyond a first threshold value or lowlights lower than a second threshold value, and if so, resetting the luminance target level from its new value to the initial value.

9. The method of claim 8 , further comprising:

determining if a scene has no highlights beyond a third threshold value that is higher than the first threshold, and if so, resetting the luminance target level from its new value to the initial value.

10. The method of claim 6 , wherein the average scene luminance level excludes at least some windows in backlit areas of the scene.

11. The method of claim 6 , further comprising:

applying tonal correction to the captured image.

12. The method of claim 11 , wherein applying the tonal correction comprises:

determining a noise level associated with the captured image; and

in response to determining that the noise level is lower than a first threshold, boosting the level of low and mid tones in the captured image.

13. The method of claim 12 , wherein applying the tonal correction further comprises:

determining a contrast level associated with the captured image;

in response to determining that the contrast level is lower than a second threshold, applying a moderate S-curve to the captured image.

14. The method of claim 12 , wherein applying the tonal correction further comprises:

determining a contrast level associated with the captured image;

in response to determining that the contrast level is lower than a third threshold, applying an aggressive S-curve to the captured image.

15. The method of claim 13 , wherein applying the tonal correction further comprises:

in response to determining that the noise level is greater than a fourth threshold, applying an S-curve to the captured image, wherein the S-curve is steeper than the moderate S-curve.