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Found 5 results

  1. Hello, We decided to build a light dome at my university, but we are having some difficulties with the lenses. We have a Nikon D7100 camera. One of our options is Sigma 70mm macro lens, it has some good reviews at different websites. However, when we asked a photographer, he suggested that we should use Nikon 105 mm instead. We are planning to photograph fingerprints on clay objects. Since our budget is tight and we don't know much about lenses, any suggestions or reviews about these or possibly other lens options is more than welcome. Thank you all! Aysel Arslan
  2. A recent capture is producing a coarse, fuzzy PTM, even though the individual RAW shots were high quality. I had trouble with the process of highlight capture because the spheres seemed to be out-of-round (distorted), and it was impossible center the guide circle on the image of the sphere. I am assuming this led to a registration problem in the PTM, hence the poor quality. These were shot on a 24–105 Canon L series zoom, on 60 mm, with the sphere right in the corner of the frame. Am I right in thinking that: 1) zooms should be avoided and macros used where possible for their typically flat fields and lack of barrel distortion. 2) the spheres should not be placed in the extreme corner of the frame but closer to the center on the edge. Feedback welcome.
  3. Hi, Apologies in advance for a rookie question, but what would this forum advice with regards to shooting RTI with a macro lens? As an archaeologist I usually shoot smaller objects with my camera attached on a tripod above the object. I am a beginner at RTI, and haven’t yet tried using macro lenses. As I am using an Olympus E-520 I was hoping that one of you would be able to direct me to the right macro lens (or lenses) best suitable for RTI. Thank you, Andreas Denmark PS: I’ve just realised that I’ve posted this question in the wrong thread, but seem to be unable to move it (by myself) to the right one. Sorry for that.
  4. For capturing high-resolution multispectral images of a 19th century landscape painting (36 x 50 inches), I found it helpful to create a spreadsheet for planning purposes, and also to supplement the shooting notes as a record of what was done. To get complete coverage of the painting at the desired resolution for RTIs and photogrammetry (500 ppi for RTIs, and up to 2600 ppi for certain details), it was necessary to take a series of overlapping images. The spreadsheet takes basic information about the object (size, material, UV sensitivity), camera and lens (format, sensor and pixel dimensions, focal length, and settings), and calculates various parameters (working distances for the camera sensor and light source, minimum size of the reflective spheres, number of images, and storage requirements) for the project, given the desired target resolution and various wavebands (UV, visible, and IR) to be captured. This information is useful for estimating the space and time requirements for capturing RTIs and photogrammetry. Since the painting is on the east coast of the U.S. and I'm in California, it was important to have a good understanding of these parameters before shipping equipment across country and for arranging studio space in which to do the work. The spreadsheet was also helpful for selecting the macro lens for the project. The storage requirements are based on a RAW image file size of 20 Mb (a slight overestimate for my 16 Mp camera) and don't take into consideration the processed file sizes. For example, generating .dng files with embedded RAW images approximately doubles the RAW file size, and exporting .jpg images adds approximately 50 percent to the storage. The final processed .ptm and .rti files range from approximately 250 Mb to 350 Mb per RTI, so accordingly, additional storage will be needed to process the files. The spreadsheet only estimates the storage needed for RAW image acquisition. Another variable is the amount of overlap for the images. For general imaging and RTIs at a given resolution, the spreadsheet uses 10 percent overlap, and for photogrammetry, it uses 66 percent overlap for the camera oriented horizontally. The spreadsheet calculates the distance to shift the camera in horizontal and vertical directions to get complete coverage of the object. It assumes three images per position for photogrammetry (horizontal and two vertical orientations) and 36 images per position for RTIs. These parameters can be adjusted for particular project needs. The input parameters are entered into the spreadsheet using metric units. A companion worksheet mirrors the format of the metric spreadsheet and automatically converts all the distances from metric to English units, for convenience. An example of the spreadsheet is attached, showing the calculations for this project. [see update below.]
  5. I recently captured over 60 Gb of images of a 36 x 50 inch 19th century landscape painting, which included both photogrammetry and over 40 RTIs in visible and two IR wavebands at resolutions ranging from about 350 to 2600 ppi. Some of the images in the RTI sequences are less than ideal, but still contain useable data, and I'm wondering whether it's better to exclude these images from the RTI processing sequence, or if I can include them with the knowledge that the processed RTI files would be slightly compromised in some areas. It's a tradeoff between using images that have relatively minor flaws to get a more complete range of light source directions in the final processed RTI files; cropping the entire set of images to eliminate discrete shadows from a few light source directions; or excluding the images that have relatively minor problems from the RTI sequence and thereby rejecting otherwise useable data. When capturing RTIs of a large surface at high resolution, it's unavoidable for some light directions to create distinct shadows from the reflecting spheres or the support, such as parts of the easel. These shadows generally affect only a small portion of the image, but cropping them out entirely would significantly reduce the area of the final RTI image, while most of the area of these images contain useful reflectance data for constructing the surface normals. Is it better to exclude these images from the RTI to avoid the shadows appearing in the RTI file, or to include them in the RTI sequence to have a more complete and accurate calculation of normal directions for the rest of the image? How fault-tolerant is the RTI Builder software to the inclusion of partly compromised images (e.g., those with discrete shadows) or to the exclusion of entire images that represent a subset of light directions? When working solo to capture the RTI image sets, it's a little more difficult to get perfect images every time--simultaneously holding the string, aiming the flash, and triggering the shutter can be a yoga challenge for some light directions. Also, when capturing macro images where the lens is close to the subject surface, there is less room for error in aiming the flash to avoid shadows. In some of the macro images, a very diffuse shadow might appear in a portion of the image that could be due to a part of the string or the pointing device on the flash falling into the path of the light source. Is it better to exclude these images entirely or can one include them for the useful data that they provide? When an RTI sequence is approaching 30 or fewer images, I'm reluctant to exclude an image that has such flaws but also contains much useable information. Can the RTI Builder software accurately calculate normals from the images for other light directions, if a portion of a single or few images in the sequence are partly affected by a diffuse shadow? Another related question is whether any pre-processing of individual images is possible to correct flaws. For example, if some images have a recurring darkened spot of unknown origin (possibly some dust on the sensor or the lens filter). Can a spot that is visible against a constant color field, such as the color checker card, be corrected in an image sequence without compromising the RTI quality?
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