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I have some low resolution images but very blurry that I wanted to improve the resolution and sharpness. On the sites out there it is fine but you have to pay to use more. If there was something like deepfacelab but focused on image improvement it would be very good , i have a good gpu

In the video, there are two layers - High and Low. High layer is the target and Low layer is the source

as far as Apply image command is concerned. Then offset is 128 and scale is 2.

To get the same result in AP Apply Image command under Filters, we have to first select the High layer.

Then from filters, click Apply image. Then click+drag the Low layer and bring it into the apply image

dialog box. Now the equations box will get enabled. click it. Now enter to make like this .

DR=((DR-SR)/2)+0.5

DG=((DG-SG)/2)+0.5

DB=((DB-SB)/2)+0.5

Blend mode is NORMAL and not SUBTRACT.

Click Apply.

Now the result is same as that of PS, in the video.

The bracketed step shown in the next line which de-saturates is not a must I think but some videos recommend it.

(To the High layer, clip a HSL adjustment layer . In the HSL, move the saturation slider to extreme left (-100%). This is to remove color info

from the High layer. Merge the HSL layer with the High layer.)

From here, the video can be followed as it is same for AP or PS.

The above text is edited today. There was a monochrome conversion(de-saturation) of the High layer using vibrance adjustment layer after

Apply image. This step was giving color cast. It is now done with an HSL adj layer with its saturation slider set to -100%. B&W adj layer can also be used.

Now there is no color cast.

The images below shows that the advanced method is really good, does not smudge away details and also does not

make highlights overly bright. I have also not used the HSL de-saturation step in the trial below.

This is the advanced highpass method described in the first thread. In one image I did about 7 radius and 14 threshold

for the blur. In another image, it was 14 radius and 14 threshold. So the second image has more sharpening. A mask was used

to bring only the face from the 2nd image and not the hair. Note that compared to the USM sharpened last image, there is

no smudging on the face and the small white highlight below the left nostril is not harsh. USM sharpened image is harsher.

Here is another screen shot of 100% or 1:1 pixel on screen. The left image is original and right image is sharpened with above method.

Before sharpening , mild colour and contrast improvement was done in LAB mode. Sharpening done last, in RGB. The background

is masked out from the sharpened layer using a mask that is white for the bird. So only the bird appears sharpened. So no unwanted

noise or grains in the background green unfocused area. D7000/ sigma 150-600 C, 1/320 sec / 1000 ISO, 600mm , handheld.

To answer your first question, it is likely that PS is using a different color space than DPP to reproduce the image.

JPEG files have less dynamic range, only 8 bits per pixel, compared to a RAW file. JPEG files are also compressed, which can dampen the details.

I think you're searching for something that doesn't really exist. As those who understand such things better than I do will tell you, a RAW file is not an image. Converting it to a viewable image involves some implicit assumptions about how the RAW data should be mapped into image data. For various reasons, including the fact that almost every camera records RAW data differently, there is not, and probably could not be, a universally accepted set of such assumptions. When you look at, say, a JPEG image, you understand that what you see depends on how a particular conversion algorithm was programmed to render a RAW file into that JPEG image. What may not be quite so obvious is that whenever you view a RAW file, either in the camera or on a computer, a similar set of algorithmic assumptions dictates what you see. You should not, for example, expect Lightroom and DPP to display a RAW file identically, any more than you would expect two different conversion algorithms to produce the same JPEG.

How do these review sites that compare camera bodies or lenses or both make a fair comparison if the output of the camera + lens combination is always altered to some extent by the software displaying the image?

Sharpening enhances the definition of edges in an image. Whether your images come from a digital camera or a scanner, most images can benefit from sharpening. When sharpening images, keep the following in mind:

The Unsharp Mask filter reproduces a traditional film technique used to sharpen edges in an image. The Unsharp Mask filter corrects blur introduced during photographing, scanning, resampling, or printing. It is useful for images intended for both print and online viewing.

Determines how far different pixels must be from the surrounding area before they are considered edge pixels and sharpened. To avoid introducing noise (in images with flesh tones, for example), experiment with Threshold values between 2 and 20. The default Threshold value (0) sharpens all pixels in the image.

When a camera or the photographer shakes while taking a picture, blurriness caused by the camera shake is introduced in the picture. It is not always possible to maintain high-shutter speeds to avoid camera shake. Taking pictures in low-light conditions may require the shutter to be open for long - resulting in shake-induced blur. Also, if the picture is taken from a moving vehicle, the image may turn out blurred due to shake caused by an uneven road.

When the Shake reduction dialog starts, Photoshop Elements places a Shake Region on the image and starts to analyze the portion of the image for shake. When analysis is done, shake correction are applied across the photo.

Despite all this I cannot reduce the amount of edge enhancement below a certain base level, so either there is an additional setting that is perhaps not exposed via the libArgus API, or there is a large amount of sharpening baked into the ISP Bayer demosaicing algorithm, or perhaps I end up with some inadvertent resizing of the image leading to resampling with a filter that includes a contrast boost.

The YUV444 Argus ISP image has an excessive amount of sharpening, with SFR contrast well above 1.4. This also shows up as visible undershoot and overshoot if we look at the image intensity profile across the edge (the edge spread function):

slanted_edge_esf855579 126 KB

I have some black level and ccm settings added in there to improve the output image color (when using yuvOneshot, for example), but the excessive local contrast enhancement is still visible without those settings.

I have reproduced the artifacts on three different camera modules: Framos FSM-IMX264, Framos FSM-IMX283 and Raspberry Pi v2 camera module (IMX219). When I let the Argus ISP process the image, then the overshoot/undershoot is clearly visible, but when I process the image myself from RAW16 there is no overshoot/undershoot (see example in my original post at the top of this thread).

I really like smart sharpen in cs2 at the moment. i think it's a lazy way compared to fine tuning unsharp mask and doing layers for various parts of an image. but for quick batch processing soft images from raw capture, i like it. 006ab0faaa