One of the most important differences is an improvement in image noise.

However, this loss is visible as image noise rather than grain.

In the second case, it may visibly affect image noise and contrast.

However, it is easy to create unwanted and conspicuous edge effects, or increase image noise.

It is also less sensitive to image noise than point-wise methods.

Dark, murky pictures with excessive image noise or "grain" will result.

It is also important when attempting sub-pixel resolution to keep image noise to a minimum.

In digital photography, image noise sometimes appears as a "grain-like" effect.

For image-based gesture recognition there are limitations on the equipment used and image noise.

Photomatix pictures after one mapping are far more dramatic, although sometimes at the expense of some details and an increase in image noise.

Many of those used in infrared astronomy are cooled with liquid nitrogen so as to reduce the image noise caused by heat.

From an artistic point of view, film grain and image noise may be desirable when creating a specific mood for an image.

Spatial video denoising methods, where image noise reduction is applied to each frame individually.

It is a widely used effect in graphics software, typically to reduce image noise and reduce detail.

In digital photography, dark-frame subtraction is a way to minimize image noise for pictures taken with long exposure times.

In continuous mode (video takes or sequential shots) the smaller sensor can be cooled better to avoid the increase of image noise.

Image noise is, of course, inaudible.

Image noise induces errors in camera positioning.

The kids would feel better, I'd be safer, and at least I wouldn't sit up all night imaging noises and intrud-ers in the house.

Additionally, image noise reduction techniques can be used to remove noise from digital images and film grain is fixed.

As with any media, they will eventually deteriorate and lose their recorded contents over time, resulting in a buildup of image noise and dropouts.

Image noise is an undesirable by-product of image capture that adds spurious and extraneous information.

Likewise, with digital cameras, images taken at higher sensitivity settings show more image noise than those taken at lower sensitivities.

Calculating the phase congruency map of an image is very computationally intensive, and sensitive to image noise.

Many independent reviews and comparisons show that image noise was improved up to 2 stops compared to the Nikon D3 or D700.