Practice English Speaking&Listening with: Real-time Edge-Aware Image Processing with a Bilateral Grid

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We introduce a new data structure, the bilateral grid,

which enables real-time, edge-aware image processing.

2D images are lifted onto a coarse, 3D grid,

where the z-component corresponds to intensity.

As a result, points across a strong edge

are distant in the grid.

We introduce slicing, an operation that

exploits this property to extract

a discontinuous, 2D image from a smooth bilateral grid.

We demonstrate a variety of real-time, edge-aware

algorithms using the bilateral grid.

We demonstrate real-time, bilateral filtering

on a noisy, 12-megapixel input.

The user can explore the parameter's base

while getting real-time feedback on the whole image.

We zoom in to show the full resolution of the image.

Real-time feedback makes it easy for the user

to fine-tune filter parameters.

We further accelerate the bilateral filter on video

by sampling a random 10% of the input pixels.

Sub-sampling causes swimming artifacts, shown on the left.

We eliminate these artifacts by applying

a temporal exponential filter, shown on the right.

We demonstrate the real-time video abstraction technique

by [INAUDIBLE] and colleagues on HD video.

We adapt real-time video abstraction

to follow a point of focus, here controlled

by the mouse pointer.

Elements that are farther away from the point of focus

are more abstracted.

We first compute the distance to the point of focus

and cross bilateral filter it with the input image

to create an adapted importance map that respects

the edges of the image.

We use this map to composite the levels of a bilateral pyramid.

The rest of the abstraction pipeline remains unchanged.

Note that our method is efficient enough

to compute five bilateral filters per frame

and allow parameter adjustment while the video plays.

We transfer the look of a model photograph

to an input video in real time.

Our result captures the tonal balance and level

of detail of the model in the spirit of the work

by Bay and colleagues.

Our method enables on-the-fly adjustment of parameters

on live, HD video.

Compared to existing techniques that

require offline processing, our approach

makes it easy to modify the level of detail

and adjust the overall tonal balance of this shot

as it plays.

We demonstrate bilateral grid painting

by locally modifying the hue while respecting

strong intensity edges.

The initial mouse click locks the brush

to an intensity level.

The brush is aware of edges and does not

paint across intensity discontinuities.

For instance, the brush does not affect the white wall

by the door.

Our method runs in real time on the GPU.

We update the entire 2-megapixel input on every frame.

We apply the same technique to locally modify

tone-mapping parameters.

We adjust exposure parameters on this 15-megapixel HDR panorama.

We paint over the gate to correct the overexposed region.

Notice how the bars are unaffected.

Similarly, the windows are unaffected

while the overexposed dome is corrected.

Our GPU algorithm updates the entire 15-megapixel image

on every frame.

We demonstrate scribble interpolation

using the bilateral grid.

We scribble on the input image, shown on the left.

The extracted influence map is shown on the right.

We use the influence map to drive a color shift.

The white scribbles cause the cloth

to change from red to blue, while the black scribbles

protect the candies.

We zoom in to show the full image resolution.

The Description of Real-time Edge-Aware Image Processing with a Bilateral Grid