> For the complete documentation index, see [llms.txt](https://developer.topazlabs.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://developer.topazlabs.com/image-models/sharpen/noise-aware-sharpen.md). # Noise-Aware Sharpen One-click sharpening that separates detail from noise ### Model Overview **Noise-Aware Sharpen** is an intelligent automatic sharpening model that uses AI-driven image analysis to evaluate both image quality and scene content before applying sharpening. Unlike traditional sharpening tools that enhance detail and noise equally, the model automatically separates true image detail from digital noise and compression artifacts before intelligently restoring clarity. The result is sharper textures, facial features, fur, and fine edges while preserving the natural character of the original image. By avoiding aggressive edge enhancement, Noise-Aware Sharpen reduces halos, oversharpening, and harsh digital artifacts commonly introduced by conventional sharpening filters. This model is especially effective for low-light, high ISO, wildlife, sports, nighttime, or grain-heavy photography where visible grain or noise is already present or intentionally part of the atmosphere of the shot. It performs best on high-resolution and production-quality imagery where preserving realism and fine detail is critical. ### Key Capabilities * One-click intelligent sharpening with no manual tuning required * Separates image detail from noise before sharpening * Preserves natural texture and realistic image character * Reduces halos, oversharpening, and sharpening artifacts ### Model Pricing
TextNumber
Output MP148162432405064100
Credits1111122335
### **Endpoint** {% hint style="info" %} In order for "auto sharpening" to be applied, `denoiseStrength`, `opacity`, `preset`, and `sharpenStrength` must be left as null. This is recommended for batch image processing with various image subject types. {% endhint %} ### Parameters `model` stringrequired Model name: "Auto Sharpen" *** `inputHeight` integeroptionaldefault="null" Input image height in pixels. *** `inputWidth` integeroptionaldefault="null" Input image width in pixels. *** `outputHeight` integeroptionaldefault="null" Output image height in pixels. *** `outputWidth` integeroptionaldefault="null" Output image width in pixels. *** `grain` booleanoptionaldefault="false" Whether to add grain to the output. *** `grainDensity` decimaloptionaldefault=0.5 Intensity of the grain effect. Range: 0.0 to 1.0 *** `grainModel` stringoptionaldefault="silver" Grain model. Possible values: "silver", "gaussian", "grey" *** `grainSize` decimaloptionaldefault=1.0 Size of the grain particles. Range: 1.0to5.0 *** `grainStrength` decimaloptionaldefault=0.5 Strength of the grain effect. Range: 0.0to1.0 *** `maskUri` stringoptionaldefault="null" URI for mask input. *** `referenceUri` stringoptionaldefault="null" URI for reference image input. *** `denioseStrength` decimaloptionaldefault="null" Amount of noise to remove from the image. Omit for non-noisy images. **Recommended: omit for automatic parameter selection.** Range: 0.0to1.0 *** `opacity` decimaloptionaldefault="null" Amount of opacity applied to the source image. **Recommended: omit for automatic parameter selection.** Range: 0.0to1.0 *** `preset` enumrequireddefault="normal" Sharpening strength. "normal" for highest fidelity,"strong" for extra, more visible sharpening. **Recommended: omit for automatic parameter selection.** Possible values: "normal", "strong" *** `sharpenStrength` decimaloptionaldefault="null" Amount of sharpening applied to the source image. **Recommended: omit for automatic parameter selection.** Range: 0.0to1.0 *** `watermark` booleanoptionaldefault="false" Whether to watermark the output. ### **Resolution Limits** * Input: 512 MP * Output: 512 MP ### Examples
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