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Up Size Down: |
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So scaling bitmap images is not a trivial problem. In fact programs like Adobe
Photoshop and Live Motion 2, Deneba Canvas and Macromedia Flash provide hybrid
image processing capabilities which allow for combining vector draw with bitmap
images in an attempt to provide the best of both worlds. In these programs users
are able to transform vector drawings with many of the familiar bitmap filters
and color corrections. Also bitmap and vector layers can be combined together with some stunning effects. But despite these advances
problems of scaling bitmap images persist. And because bitmap graphics comprise over 2/3rds of all images used
on the Web, upsizing and downsizing of bitmap images is a major problem encountered by Web and graphic designers
everywhere. |
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their superior results. As well the resizing algorithms used by the major bitmap editors have also improved based on our recent tests. Specifically for the upsizing we have taken a 300 x 200 pixel image and enlarged it by factors of 5x and 7x (1500 x 1000 pixels or 25x larger filesize and 2100 x 1400 pixels or 49x larger filesize respectively). For many of the methods we found this was the practical upper limit for enlargement as edge sharpness and color bleeding became very notable in the 6x or greater enlargements. Only VFZoom and Genuine Fractals could push beyond this point. However, as can be seen from Table 1, the fidelity in rendering colors was very favorable by all the methods - unfortunately, this accuracy fell of notably in downsizing. Color Fidelity Tests After upsizing and downsizing we took readings use Adobe PhotoShop 7's Color Sampler Tool at many points in the re-sized images and compared them to equivalent readings from the original image. The results were quite encouraging on upsizing. All upsizing methods produced excellent color fidelity. Table 1 shows just 4 of the 16 points sampled in each image. In general many results were within 3 to 10 points of the true value - it is almost impossible to discern any difference with the naked eye. However, there is a tendency to make the image slightly brighter which is even more pronounced when the original hue is already bright. |
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However, about 25% of the time colors were rendered darker. Rarer still were the occasions when color readings jittered - brighter in one color hue, darker in another. Table 2 summarizes the color fidelity results when downsizing. Here measurements were a bit more problematical as the downsizing was by a factor of nearly 1/5 (1/25 the filesize) from the original - so many features got "imploded". Still the results were fairly consistent across about 20 readings. As in upsizing, solid areas of color were preserved very well as seen in the first column pure white of Table 2. But edge colors tended to shift more as different hues were forced to mix in compression. Thus color fidelity was notably worse for downsizing as images took on a slight grayish pallor - particularly photo images having many detail colors as in our sample on the "pebble" background. In sum, upsizing color fidelity is uniformly very good while downsizing loses fidelity at the edges and color mixing areas to the degree of just noticeable shifts either brighter or darker depending on the contrast in the local region. Genuine Fractals, VFZoom were first and second consistently in both up and down sizing color fidelity. The third best for upsizing were very close with Bicubic methods nosing out the others. In contrast, for downsizing color fidelity, the Jasc Bilinear method seemed to hone in better than the other methods for third spot. Image Fidelity |
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the Genuine Fractals program. This was the only method we could push confidently past the 5X limit without getting significant color bleed or edge softening. VFZoom was distinctly better than the remaining methods often pushing into the 6x to 7x range before surfacing notable distortions. But be advised, even Genuine Fractals cannot match the edge and overall image fidelity of SVG and other vector graphics. To repeat, vector graphics edges and colors are bang on 1x to 100x. But of course, with the digital camera revolution more images are coming to graphic artists in bitmap form. For third place on upsize image fidelity, the choice is difficult but as in upsizing color fidelity the Bicubic methods appear to be better. In contrast, on downsizing image fidelity was disappointing for all the methods even at 1/5x. Every method tended to introduce softness and or jaggies at the edges. Pixel checkering was another phenomenon. For top 3 methods its your choice among the Bilinear methods, VFZoom and Genuine Fractals. In fact for both upsizing and downsizing, it is distinctly the user choice on image sharpness and fidelity. Some designers can tolerate more sedge softness but no color bleed. Others cannot tolerate jaggies. However, testing showed the upper bound to be about 1/2.5x when some of these distortions start to appear notably. In general, it is safer to upsize than downsize an image. Conclusion Since upsizing up to 5x is possible with most good bitmap editors (and can be pushed beyond that with the Genuine Fractals $200 or VFZoom $120 Adobe plugins), digital camera buyers looking for a bargain are advised to layoff the expensive multi-megapixel units. Instead concentrate on a digital camera in the 1-2Mpixel range with superior optics, zoom range, color fidelity and overall usability. Likewise, graphics and design shops with thousands of images and dozens of users should consider Genuine Fractals and VFZoom server versions, which can store medium scale starter images and then confidently upscale by 5-7 times (or more in the case of Genuine Fractals) and downsize by up to 40%. If lots of downsizing is required, store second starter downscale or thumbnail images. But the savings in storage space and processing time can be considerable. Remember, the color fidelity on upsizing is excellent. So designers can do most of their color and filter edits at low resolution and have confidence the colors will be maintained on the upsizing step. In fact, the only editing that should be done at full resolution would be borders and straight lines. Doing most of the edits on an image 1/25 the final filesize (assuming an average 5 times enlargement) can save a lot of processing and wait time. So software re-sizing, especially upsizing, may just turn the graphics world upsize down. Jacques Surveyer is a consultant and photographer, he can be reached at jbsurv@thePhotoFinishes.com |
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References: Compression Algorithms, A.Hassan, Addison Wesley |
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