Focus (or sharpness) in a digital image is created and controlled by the amount of edge contrast that exists between adjacent pixels, especially along high-contrast edges. Soft-focus images have wider, lower-contrast edges within the image. Sharp-focused images have image elements with higher contrast and narrower edges.
Sharpening is basically an edge contrast enhancement technique. When you sharpen an image, you increase the contrast between its adjacent pixels. Sharpening also tends to narrow the amount of contrast along edges. Nearly all digitally captured images require at least some sharpening, because the very process of digital capture tends to be soft. Prior to sharpening, the edges are obvious but somewhat smooth. After sharpening, you will notice that the contrast between the pixels along the high-contrast edges is noticeably increased. This creates the impression of enhanced focus or sharpness. You will want to carry this focus or sharpness through to the printing process, because printing tends to soften each of these edges.
Unlike noise, which is typically extra, unwanted data represented by a pattern, sharpening is considered an asset. However, sharpening can be your enemy if it is applied to noise in an image. Noise is often created by pattern elements that have high-contrast edges, and because sharpening tends to increase contrast along these edges, sharpening can exacerbate the noise and its unwanted patterns in your image. Because of this potentially damaging process, one of the early investigations you should make into any image correction workflow is to inspect for any unwanted noise that should be removed prior to sharpening.
There is one other big difference between noise reduction and sharpening. Mitigating noise, which usually involves some sort of smoothing process, tends to increase the number of intermediate tonal values present in an image, whereas sharpening tends to decrease the number of tonal values. Because of this difference, you should employ noise reduction near the beginning of your workflow, because noise reduction will provide you with more tonal values with which to accomplish your image-editing and color-correction chores. Sharpening conversely should typically be applied at the very end of your imaging workflow, because the process of sharpening tends to decrease the tonal values in your image. In fact, I recommend that you save unsharpened, colorcorrected and edited versions of your image as archive images from which you can create sharpened copies for various purposes.
Sharpening is basically an edge contrast enhancement technique. When you sharpen an image, you increase the contrast between its adjacent pixels. Sharpening also tends to narrow the amount of contrast along edges. Nearly all digitally captured images require at least some sharpening, because the very process of digital capture tends to be soft. Prior to sharpening, the edges are obvious but somewhat smooth. After sharpening, you will notice that the contrast between the pixels along the high-contrast edges is noticeably increased. This creates the impression of enhanced focus or sharpness. You will want to carry this focus or sharpness through to the printing process, because printing tends to soften each of these edges.
Unlike noise, which is typically extra, unwanted data represented by a pattern, sharpening is considered an asset. However, sharpening can be your enemy if it is applied to noise in an image. Noise is often created by pattern elements that have high-contrast edges, and because sharpening tends to increase contrast along these edges, sharpening can exacerbate the noise and its unwanted patterns in your image. Because of this potentially damaging process, one of the early investigations you should make into any image correction workflow is to inspect for any unwanted noise that should be removed prior to sharpening.
There is one other big difference between noise reduction and sharpening. Mitigating noise, which usually involves some sort of smoothing process, tends to increase the number of intermediate tonal values present in an image, whereas sharpening tends to decrease the number of tonal values. Because of this difference, you should employ noise reduction near the beginning of your workflow, because noise reduction will provide you with more tonal values with which to accomplish your image-editing and color-correction chores. Sharpening conversely should typically be applied at the very end of your imaging workflow, because the process of sharpening tends to decrease the tonal values in your image. In fact, I recommend that you save unsharpened, colorcorrected and edited versions of your image as archive images from which you can create sharpened copies for various purposes.
Sharpening
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