## Scanning negative 35mm: color accuracy, color balance, film bias

My question is about scanning color 35mm film. I use professional film (Portra 400) and a very good lab. I get consistent results and prints.

This year i have invested in semi-pro or pro scanner Reflecta 10T with expensive SilverFast Ai Studio 8. And I intend to scan 35mm film for printing purposes. My goal is to have very high quality 30 x 40 inch prints.

Scanner is giving me fantastic results: 230 MB, 7052 x 4715 pixels (33,5 MP) TIFFs with great natural/crisp film grain and overall great look.

BUT the colors are off. Always. I use NegaFix (piece of SilverFast) with the correct Portra 400 profile and I try to put accurate WHITE, BLACK and GREY points (where they are in picture) but I never get consistent and real results. Pics are never “right”, always off, always to bright or to warm (to cold).

I read all forums about how scanning is difficult and about SilverFast and VueScan, Color perfect and Photoshop but everywhere people have problems getting colors right.

My questions are:

1. Should I just continue this guessing game and try to somehow spot the right color everytime?

2. Have you tried putting Grey Card 18% and set this as a correct exposure in scanning soft or Lightroom and color balance from there?

3. Have you tried putting Color Balance Card (White, Black, Grey) to help scanning software determine exposure and color balance and color balance from there?

4. Have you tried X-Rite’s Color Checker Passport or other color calibration target to set full color correction this way?

5. If yes, what about film bias. (Portra 160 more pastel, Ektar 100 a lot more vivid) Wouldn’t it just get you to the POINT ZERO with film where you have no film specific properties?

The goal is to have as close to 35mm film scanned image as possible, without any interpretation. Just what you get from film processed neutral and printed neutral. To see real film color specific for it’s kind. I just want to see good Portra 400 on my screen.

## Probability of detecting small bias in a die in the low confidence regime

We are given a biased $$m$$-sided die: one of the sides has probability $$\frac{1}{m} + \gamma$$ and all the rest have probability $$\frac{1}{m} – \frac{\gamma}{m-1}$$ each. The goal is to figure out which of the sides is biased given $$t$$ independent throws. Naturally, the optimal way to do that is to output the side with the largest count (with randomized tie breaking).

I’d like to give a lower bound on the success probability of this method when the number of throws is too small to get high probability of success. More formally, assume that $$\gamma \leq \frac{1}{\sqrt{tm}}$$ (which is roughly the standard deviation of each of the counts). You can also assume that $$t\geq c m \log m$$ (for any fixed constant $$c$$). In the case of $$m=2$$ a simple calculation shows that success probability in this regime is $$\geq \frac{1}{2} + \Omega(\sqrt{t}\gamma)$$. More generally, based on some back-of-the-envelope calculations and simulations the answer should be $$\geq \frac{1}{m} + \Omega(\sqrt{t}\gamma)$$. However, I do not see a formal argument that proves this (and a direct calculation in this case seems very painful).

The question can also be reduced to the following question about a regular unbiased die (or the standard balls-and-bins model). What is the probability that the first count is exactly equal to the maximum of the rest of the counts?

Would be grateful for references or analysis suggestions.

## In a survey, will the color of the thumbs for choices bias the responses?

Many companies add satisfaction surveys to their emails and thank you pages. In the case of a thumbs up/thumbs down survey, is it smart to use color to increase the amount of responses?

I see two main disadvantages with the color red/green: in Asia, colors are used in the contrary and the colors hardly ever fit with the branding of the company. So survey usually looks unprofessional.

The advantage I see is that it is faster to scan for the user what is the “good” answer or the “bad”, because colors add redundancy to the meaning.

What do you think is best, red/green option or one color option?

## [ Politics ] Open Question : I’m working on a paper about possible news bias I just need a small bit of info from all of you.?

1. What state you live in. 2. What source (or sources) you generally use when looking at the news. 3. Who you supported and or voted for in the 2016 election. 4. What you identify as on the political spectrum.