HAPPYF-067 คล้าย stars and swaying moons

HIMEMIX-163 Exploring the Benefits of a Balanced Lifestyle for Overall Well-being

2 Jul 2009

STAR-167 Artist Yasuzan Nemui traverses Japan in a shameful journey!?

4 Jul 2009

BKSP-205

3 Jul 2009

RCT-121 The ultimate fantasy invention series special edition: Body switch.

3 Jul 2009

DVDES-187 The Majestic Mirror in Kobe Harbor Town offers a delightful dining experience for the young ladies!

4 Jul 2009

STAR-166 Respectful appreciation for the talent and dedication of actress Kotono.

4 Jul 2009

BKSP-204

3 Jul 2009

DANDY-142

3 Jul 2009

GAR-108 for the "pixelated" phenomenon of a small picture being downscaled to a newer, smaller resolution where dimensions are different or "stretched" is called "quantization noise" and is a manifestation of aliasing that occurs when compressing image data. It is also called "pixelization" or "pixelated" due to the pixel's being enlarged during magnification steps on resize via applying bicubic or bilinear interpolation etc things like this, because it directly applies to the pixels and making them sort of look like visible, singular points on display rather something smooth, something coherent etc. wow, that was a big huge long sentence, i know, but that is as accurate as i can make it for you to understand. Distorted or more jaggy pixels are due mainly pixelization on scaling/resizing images. A "stretched" resolution is supposed to refer to the aspect ratio of the display being unsupported in current resolution of operating system, not matching but this also is directly linked to the quantization noise on quantization or on resizing/reconstruction downscaling pixel data. And when you have a model or image or texture being downscaled to a new dimension being different in ratio from the initial, then this manifests even more ,causes worse "pixelation" and amplification of pixellation. Correct is to use values matching and ratios matching from initial upload/resolution of inch and pixel/sqpc measurements. scaling down is not so much a issue unless ai like waifu2x is not implemented to address it because they train data on how to keep the rest of image 3D/HDR VS that rather then being absolutely perfect or "downscaled properly" without AI, it would be like sequencer/peak samples resizing an audio signal to a new rate, causes heaps of aliasing / corrupt/pixelated view, that way is due to the scaling methoding not be anti aliased or smoothed out proper. fact is, sometimes people use upscaling to make image larger which you cant downsample back to initial size and get same image back, it will be deformed slightly because of the filtering method on initial upscaling, so its also important to know upfront scaling is if you need to perform a downscaling on it or not, you have to consider something like that or plan ahead. Waifu2x also has a seam issue, it leaves a seam when you upscale like downsample/upsample usage, like Nvidia's DSR high res output but which is with a tiny seam of sample pixels causes a repeat/reference issue, if you dont plan upfront, like if you upscale image via waifu2x etc, then you resize to get it back to normal, it will be more distorted for sure, because of too much interpolations configs cumulative in residual data, in reality. To fix or reduce the "pixelated" (or misshaped/pixelation) phenomenon during downscaling of an image to a smaller resolution, it is important to implement "anti-aliasing" algorithms. Anti-aliasing can smooth out the edges and compressions of images, ensuring they look more transparent. Anti-aliasing techniques include: like upscaling and downscaling, like ALiased (the assumption is aliasing since waifu2x is half ML/neural based and one not) or FS/FSX - texture filtering attempts to minimize pixelation across all dimensions of pixels. So to really mitigate pixelation, one must adhere to anti-alising issues by ensuring consistent sampling rates across dimensions. You can also use AI models like Waifu2x, which are widely used for resizing, to ensure higher quality and minimize pixelation. Waifu2x can help in smoothing upscaling as well as downscaling images, providing a more natural and coherent display of images. In conclusion, to minimize pixelation on downscaling, one should implement anti-aliasing techniques or use AI models to ensure higher quality image output and minimize distortion during resizing.

3 Jul 2009

GAR-106

3 Jul 2009