Adjusting the sharpness of a digital image
The sharpness of a digital image is adjusted according to defined aim subject and background sharpness levels. An image segmentation process is used to segment an input digital image into a subject region and a background region. The subject and background regions are analyzed to determine corresponding subject and background sharpness levels. An enhanced digital image is formed wherein the sharpness of the subject region is adjusted responsive to the subject sharpness level and the aim subject sharpness level, and the sharpness of the background region is adjusted responsive to the background sharpness level and the aim background sharpness level. In some embodiments, the input digital image is analyzed to determined a scene type classification and the aim subject and background sharpness levels are defined in accordance with the determined scene type classification.
1. A method for adjusting the sharpness of a digital image, the method being implemented at least in part by a data processing system, comprising:
receiving an input digital image;
applying an image segmentation process to segment the input digital image into a subject region and a background region;
automatically analyzing the subject region to determine a subject sharpness level and automatically analyzing the background region to determine a background sharpness level;
defining an aim subject sharpness level for the subject region and an aim background sharpness level for the background region;
processing the input digital image to form an enhanced digital image wherein the sharpness of the subject region is adjusted responsive to the subject sharpness level and the aim subject sharpness level, and the sharpness of the background region is adjusted responsive to the background sharpness level and the aim background sharpness level; and
storing the enhanced digital image in a processor-accessible memory.
2. The method of claim 1 wherein the aim subject sharpness level and the aim background sharpness level are defined responsive to a scene classification.
3. The method of claim 2 wherein the scene classification is selected by a user by means of a user interface.
4. The method of claim 2 wherein the scene classification is determined by automatically analyzing the input digital image or responsive to metadata associated with the input digital image.
5. The method of claim 2 wherein the aim subject sharpness level and the aim background sharpness level are defined to provide a predetermined sharpness difference between the subject and the background, and wherein the predetermined sharpness difference is responsive to the scene classification.
6. The method of claim 1 wherein the aim subject sharpness level and the aim background sharpness level are defined responsive to the determined subject sharpness level or the determined background sharpness level.
7. The method of claim 1 wherein the aim subject sharpness level and the aim background sharpness level are defined responsive to a user preference study.
8. The method of claim 1 wherein the automatic analysis of the subject region or the background region to determine the corresponding subject sharpness level or background sharpness level includes:
determining an edge map of edges in the subject region or background region, wherein the edge map has edge values indicating edge strength;
identifying strong edges having edge values that exceed a strong edge threshold; and
determining the corresponding subject sharpness level or background level by computing an average of the edge values for the identified strong edges.
9. The method of claim 8 wherein the strong edge threshold is determined based on a edge value histogram, the edge value histogram being a histogram of the edge values in the corresponding subject region or background region.
10. The method of claim 9 wherein the strong edge threshold corresponds to a predefined percentile of the edge value histogram.
11. The method of claim 1 wherein the sharpness of the subject region is adjusted by applying an unsharp masking operation, and wherein one or more parameters used in the unsharp masking operation are adjusted responsive to the subject sharpness level and the aim subject sharpness level.
12. The method of claim 11 wherein the one or more parameters that are adjusted include a gain parameter or filter coefficients in a convolution kernel.
13. The method of claim 1 wherein the sharpness of the background region is adjusted by applying an unsharp masking filter operation, and wherein one or more parameters used in the unsharp masking operation are adjusted responsive to the background sharpness level and the aim background sharpness level.
14. The method of claim 13 wherein the one or more parameters that are adjusted include a filter strength parameter or filter coefficients in a convolution kernel.
15. The method of claim 1 wherein the sharpness of the background region is adjusted to blur the background, and wherein the adjustment of the sharpness of the background region to includes iteratively applying low-pass filtering and resizing operations until an appropriate amount of blur has been achieved.
16. The method of claim 1 wherein the output digital image is determined using a data processor in an image capture device used to capture the input digital image.
17. The method of claim 1 wherein the output digital image is determined using a data processor in a host computer, a kiosk or a network server.